Generating Enhanced Digital Images Using Context-Aware Sensors and Multidimensional Pose Input

Abstract

The present disclosure relates to generating enhanced digital images using context-aware sensors and multi-dimensional gesture inputs. The present disclosure relates to systems, methods, and non-transitory computer-readable media for generating enhanced digital images using context-aware sensors and multi-dimensional gesture inputs on digital images. In particular, the disclosed system can provide dynamic sensors on digital images within a digital enhanced user interface (e.g., a user interface without visual elements for modifying parameter values). In response to selection of a sensor location, the disclosed system can determine one or more digital image features at the sensor location. Based on these features, the disclosed system can select parameters and map them to movement directions. Additionally, the disclosed system can identify user input gestures including movement in one or more directions on the digital image. Based on the movement and one or more features at the sensor location, the disclosed system can modify parameter values and generate enhanced digital images.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of digital images and, more particularly, to the generation and editing of enhanced digital images. Background Art

[0002] In recent years, there have been significant improvements in software and hardware platforms for editing digital images. In fact, conventional digital image editing systems can provide a variety of digital image editing tools that allow users to personalize, improve, and transform digital images. For example, conventional digital image editing systems can modify the hue, saturation, and brightness of a digital image, crop / replace objects depicted in the digital image, and / or correct flaws in digital images captured by client devices.

[0003] Despite these advancements, there are still many problems with conventional digital image editing systems - particularly in terms of the efficiency, flexibility, and accuracy of operations. For example, in terms of efficiency, conventional digital image editing systems require a significant amount of time and user interaction to modify digital image parameters. For example, many conventional digital image editing systems use sliders or similar visual controls to change various parameters of a digital image. Such an approach is indirect, unintuitive, takes up valuable screen space, and detracts from the concentration of the digital image itself. For example, to modify exposure, contrast, shadows, highlights, and black and white cut-off points, some conventional systems use six separate slider elements. As a result, conventional digital image editing systems require excessive user interaction to locate (e.g., navigate various drop-down menus), select, and modify different sliders (or other individual controls) to generate a modified digital image.

[0004] In addition, conventional digital image editing systems are inflexible. For example, conventional digital image editing systems do not scale well to small screens, such as mobile devices. In fact, due to the screen space dedicated to chrome, drop-down menus, sliders, or other visual user interface controls, conventional digital image systems typically offer limited or reduced options on mobile devices (e.g., smartphones). Additionally, due to the complexity of interacting with rigid user interface elements to change various digital image parameters, conventional digital image editing systems are often inaccessible to (and not used by) novice users.

[0005] In addition to concerns about efficiency and flexibility, conventional digital image editing systems often produce inaccurate results. In fact, since slider (or other user interface) elements are often difficult to find and intuitively utilize, client devices routinely generate digital images that do not accurately reflect the desired / required modifications. For example, performing a change in the brightness of a specific tonal region (while leaving other tonal regions unmodified) may require a series of specific changes to various individual sliders. Due to the difficulty of accurately entering such modifications, conventional digital image editing systems often generate digital images that do not accurately reflect the desired modifications.

[0006] Accordingly, there are several technical problems with conventional digital image editing systems. SUMMARY OF THE INVENTION

[0007] One or more embodiments provide benefits and / or solve one or more of the foregoing or other problems in the art with systems, methods, and non-transitory computer-readable storage media that effectively generate enhanced digital images using context-aware sensors and multi-dimensional gesture inputs. In particular, in one or more embodiments, the disclosed systems utilize a digital image enhancement user interface that does not include slider elements, but rather uses intuitive two-dimensional gestures entered directly on the digital image to control multiple parameters of the digital image. Additionally, the disclosed systems can utilize dynamic sensors that track user movement relative to the digital image, detect aspects of the underlying image regions, and react to the associated image content to generate enhanced digital images. By using dynamic sensors that determine digital image features at the sensor location and using gesture inputs on the digital image to modify corresponding digital image parameters, the disclosed systems can effectively, flexibly, and accurately generate enhanced digital images.

[0008] Additional features and advantages of one or more embodiments of the present disclosure will be set forth in the description below, and in part will be apparent from the description, or may be learned by practice of such example embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The detailed description is described with reference to the accompanying drawings, in which:

[0010] Figure 1 illustrates an example environment in which a digital image enhancement system operates according to one or more embodiments;

[0011] Figure 2 illustrates a diagram of a process for generating an enhanced digital image according to one or more embodiments;

[0012] Figure 3The figure shows a schematic diagram for determining digital image features at a sensor position according to one or more embodiments;

[0013] Figure 4 The figure shows determining a parameter value from a user input gesture on a digital image according to one or more embodiments;

[0014] Figure 5 The figure shows selecting a parameter to be modified based on features detected at a sensor position of a digital image according to one or more embodiments;

[0015] Figure 6 The figure shows modifying a parameter specific to features detected in a digital image at a sensor position according to one or more embodiments;

[0016] Figure 7 The figure shows modifying one or more parameters based on a user input gesture and multiple styles on a digital image according to one or more embodiments;

[0017] Figure 8 The figure shows various input modes utilized to generate an enhanced digital image according to one or more embodiments;

[0018] Figures 9A - 9B The figure shows a digital image enhancement user interface for generating an enhanced digital image according to one or more embodiments;

[0019] Figure 10 The figure shows a digital image enhancement user interface for generating an enhanced digital image according to one or more embodiments;

[0020] Figure 11 The figure shows a digital image enhancement user interface for switching between displaying a digital image and displaying an enhanced digital image according to one or more embodiments;

[0021] Figure 12 The figure shows a schematic diagram of a digital image enhancement system according to one or more embodiments;

[0022] Figure 13 The figure shows a flowchart of a series of actions for generating an enhanced digital image according to one or more embodiments;

[0023] Figure 14 The figure shows a flowchart of a series of actions for generating an enhanced digital image according to one or more embodiments; and

[0024] Figure 15 The figure shows a block diagram of an example computing device according to one or more embodiments. Detailed Description

[0025] One or more embodiments of the present disclosure include a digital image enhancement system that utilizes context-aware sensors and multi-dimensional pose inputs on a digital image to effectively generate enhanced digital images. In particular, the digital image enhancement system can improve digital image editing by utilizing a digital image enhancement user interface without slider controls (or other visually selectable control elements). For example, in some embodiments, the digital image enhancement system utilizes multi-dimensional poses on a digital screen depicting the digital image to modify parameters of the digital image. Additionally, the digital image enhancement system can utilize a dynamic sensor that determines characteristics of a selected location of the digital image. The digital image enhancement system can dynamically determine modifications based on underlying characteristics and multi-dimensional pose inputs on the digital image. By utilizing sensors and user input poses on top of the digital image itself (without intrusive selectable controls), the digital enhancement system frees up screen space to efficiently and flexibly generate accurate digital image modifications.

[0026] For illustration, in one or more embodiments, the digital image enhancement system identifies a user selection of a first location (e.g., a sensor location) on the digital image within the digital image enhancement user interface. The digital image enhancement system can analyze the first location of the digital image and identify one or more characteristics of the digital image at the first location (e.g., an object or hue depicted at the first location). In some embodiments, the digital image enhancement system detects a user input pose that includes a movement to a second location of the digital image enhancement user interface. Based on the movement to the second location and one or more characteristics of the digital image, the digital image enhancement system can determine modifications to one or more parameters of the digital image. Additionally, the digital image enhancement system can generate an enhanced digital image by applying the modifications of the one or more parameters to the digital image.

[0027] As just mentioned, a digital image enhancement system can modify digital image parameters using a user interface without sliders and other conventional visual selectable elements. In particular, in one or more embodiments, the digital image enhancement system can detect a user input gesture that includes movement in multiple directions to determine parameter values for modifying the digital image. By way of illustration, the digital image enhancement system can determine a user input gesture that includes a first movement in the horizontal direction. Based on the first movement in the horizontal direction, the digital image enhancement system can determine a first parameter value for modifying the digital image (e.g., a change in saturation). Similarly, the digital image enhancement system can detect that the user input gesture includes a second movement in the vertical direction. Based on this second movement, the digital image enhancement system can determine a second modification parameter value for modifying the digital image (e.g., a change in hue). Thus, the digital image enhancement system can allow a user to modify one or more parameters of a digital image without having to navigate and utilize multiple different menus and sliders in a multi-step workflow. Instead, the digital image enhancement system can allow the user to directly and intuitively interact with the image to perform editing.

[0028] As discussed above, the digital image enhancement system can also utilize context-aware sensors to determine features of a digital image and generate an enhanced digital image. For example, in one or more embodiments, the digital image enhancement system provides a transparent sensor for display that follows dynamic user interactions within the digital image enhancement user interface. In response to a user selection of the sensor location, the digital image enhancement system can determine the features of the digital image at that location. Specifically, the digital image enhancement system can isolate the region of the digital image surrounded by the transparent sensor and analyze the region (e.g., using a color analysis model and / or an object identification model). Thus, the digital image enhancement system can determine various features such as color, hue, brightness, saturation, or the objects depicted in the digital image at the selected location.

[0029] When using context-aware sensors to identify features at a selected location of a digital image, the digital image enhancement system can use the identified features as a basis for modifying the digital image. For example, the digital image enhancement system can use the features at the sensor location to select parameters and map the parameters to specific aspects of the user input gesture. By way of illustration, the digital image enhancement system can detect the hue within a selected region of the digital image. Based on the detected hue, the digital image enhancement system can map a first parameter to movement in the horizontal direction (e.g., map a saturation change to horizontal movement), and map a second parameter to movement in the vertical direction (e.g., map a hue change to vertical movement). Thus, based on intuitive gesture input on the digital image and the selected location, the digital image enhancement system can intelligently detect the features that the user is attempting to modify, and modify the digital image without interacting with any sliders or other visual controls.

[0030] In one or more embodiments, the digital image enhancement system also utilizes various modes to provide additional control over parameters for modifying a digital image. For example, the digital image enhancement system can utilize different input modes corresponding to different parameters and / or features that allow a client device to select which features or parameters to utilize when generating an enhanced digital image. By way of illustration, the digital image enhancement system can include: a color mode (e.g., which maps hue to a first direction of movement and saturation to a second direction of movement), a light mode (e.g., which maps brightness to a first direction of movement and contrast to a second direction of movement), a color curve mode (e.g., which maps a direction of movement to a variable of a color curve), or a structure mode (e.g., which focuses on detecting and modifying underlying objects or structures depicted in the digital image), or a style mode (e.g., which blends between predefined styles or filters based on a user input gesture on the digital image). As discussed below, the digital image enhancement system can utilize various different predefined or user-defined input modes to edit a digital image. Additionally, the digital image enhancement system can automatically determine an input mode based on various factors (e.g., based on digital image content or historical mode usage).

[0031] As mentioned above, the digital image enhancement system offers many advantages compared to conventional systems. For example, by utilizing context-aware sensors and / or multi-dimensional gesture inputs to generate an enhanced digital image, the digital image enhancement system can improve efficiency relative to conventional digital image editing systems. In fact, as mentioned above, the digital image enhancement system can avoid sliders or other visual elements that are utilized by conventional systems to modify digital image parameters. The digital image enhancement system can utilize intelligent sensors to determine which parameters a user is attempting to modify within a digital image. Additionally, the digital image enhancement system can utilize intuitive two-dimensional gesture inputs on top of the digital image itself to determine how a user is attempting to modify those parameters. Thus, the digital image enhancement system can significantly reduce the time and number of user interactions required to generate an enhanced digital image. In fact, based on selections and movements on the digital image, the digital image enhancement system can perform complex modifications that would require dozens of user interactions with drop-down menus and sliders to accomplish using a conventional system.

[0032] In addition to efficiency improvements, digital image enhancement systems are also more flexible than conventional systems. By leveraging a digital image enhancement user interface that does not include sliders, drop-down menus, chrome elements, or other toolbar elements that take up screen space or obscure the image, digital image enhancement systems can operate seamlessly on different client devices, including mobile devices such as smartphones or tablets. Additionally, by using context-aware sensors, digital image enhancement systems can perform flexible modifications specific to features depicted in the digital image, such as objects or colors at a specific dynamic sensor location. Furthermore, since digital image enhancement systems do not have to rely on various sliders to modify different parameters, they are more accessible to client device users of all skill levels.

[0033] Moreover, digital image enhancement systems also improve accuracy relative to conventional systems. In fact, by leveraging sensors and intuitive multi-dimensional input, digital image enhancement systems can intuitively perform specific, complex modifications to digital images that accurately reflect the desired changes. To illustrate, using a conventional system to modify the brightness of a specific tonal range within a digital image while leaving other tonal ranges unchanged would require the user to locate, modify, and balance multiple sliders (or other user interface elements). Users often have difficulty identifying and accurately adjusting the various different visual elements to produce the desired result. In contrast, a digital image enhancement system can perform such a modification based on a selection of the location of the tonal range depicted in the digital image and a user input gesture on the digital image itself. Thus, digital image enhancement systems can produce more accurate digital image enhancements.

[0034] As illustrated by the foregoing discussion, the present disclosure uses various terms to describe the features and advantages of digital image enhancement systems. More detailed information regarding these terms is now provided. For example, as used herein, the term "digital image" refers to any digital symbol, picture, icon, or illustration. For example, the term "digital image" includes digital files having the following or other file extensions: JPG, TIFF, BMP, PNG, RAW, or PDF. The term "digital image" also includes one or more images (e.g., frames) within a digital video. Thus, although much of the description herein is presented in terms of digital images, it should be understood that the present disclosure can also be applied to editing digital video. Additionally, as mentioned above, digital image enhancement systems can generate enhanced digital images. As used herein, an "enhanced" digital image refers to a digital image having modified pixels. For example, an enhanced digital video includes a digital video in which one or more parameters (e.g., hue, brightness, saturation, exposure) have been adjusted, changed, or modified.

[0035] As used herein, the term "parameter" (or "digital image parameter") refers to a visual characteristic, property, or setting of one or more pixels of a digital image. In particular, the parameters of a digital image include adjustable characteristics or settings that affect the appearance of the digital image. For example, parameters can include: hue (e.g., a color on a color wheel), saturation (e.g., the intensity or purity of a hue from a gray-scale tone to a pure color), brightness (e.g., the relative lightness or darkness of a color from black to white), contrast (e.g., a measure of the difference between bright and dark pixels in a digital image), or exposure (e.g., a scaling factor of the brightness on a digital image). Similarly, parameters can include: shadow parameters (e.g., for adjusting the shadow or dark tone areas of an image), highlight parameters (e.g., for adjusting the bright tone areas of an image), black point (e.g., a black cut-off point), white point (e.g., a white cut-off point), vividness (e.g., a measure of the intensity of a soft color as opposed to a highly saturated color), sharpness, color temperature, or chromaticity (e.g., a measure of the mixture of a color with white). Parameters can also include adjustable variables related to a color curve (e.g., edit points for modifying the curve and / or affecting the shadow, highlight, black / white cut-off parameters of the color curve).

[0036] In one or more embodiments, a parameter has a corresponding parameter value. As used herein, "parameter value" refers to a measure, metric, level, or quantity of a parameter. For example, a hue parameter can include a hue value (e.g., a number representing a color on a 360-degree color wheel). Similarly, a saturation parameter can include a saturation value (e.g., a percentage of saturation or some other measure).

[0037] As used herein, the term "modify" means to change or alter. In particular, modifying a parameter includes changing or altering the parameter of a digital image. For example, modifying a parameter includes changing a parameter value (e.g., a saturation value, a brightness value, or a hue value). As outlined in more detail below, a digital image enhancement system can determine a modification by selecting one or more parameters to change (e.g., based on the characteristics of the digital image) and identifying new parameter values (e.g., based on different dimensions of a user input gesture).

[0038] As mentioned above, a digital image enhancement system can utilize a sensor when generating an enhanced digital image. As used herein, a "sensor" (or "context-aware sensor" or "transparent sensor") refers to a user interface element that indicates a location or region of a digital image to be analyzed. In particular, a sensor can include a user interface element that defines a location or region of a digital image, where underlying content is analyzed to determine parameters of the digital image to be modified. In some embodiments, the sensor is transparent (i.e., translucent, as it reveals or displays a portion of the digital image that overlaps the sensor), such as a transparent circle that allows a user to see the underlying digital image while identifying the location to be analyzed (i.e., the sensor location).

[0039] As mentioned above, a digital image enhancement system can analyze a region corresponding to a sensor to identify one or more features. As used herein, a "feature" of a location of a digital image refers to one or more visual characteristics depicted in a region of the digital image. For example, a feature can include a measure of the color (e.g., hue), saturation, or luminance of pixels within a region or location of the digital image. By way of illustration, a feature can include a statistical measure, such as an average or standard deviation of pixel hue, saturation, and / or luminance within a region. A feature can also include a range, such as a hue range, a luminance range (e.g., a tonal range such as a shadow tone, a midtone, or a highlight tone), or a saturation range. A feature of a location of a digital image can also include an object depicted in the location of the digital image. In some embodiments, a feature also includes other characteristics, such as a geographical location or time depicted in the digital image (e.g., a season, a date, or a time of day).

[0040] As used herein, the term "user input gesture" refers to an interaction with a user of a computing device. In particular, a user input gesture can include an interaction with a user that identifies a location associated with a graphical user interface depicted on a display screen of the computing device. For example, a user input gesture on (or "above" or "on") a digital image can include a swipe gesture on a portion of a touch screen that displays the digital image (e.g., a swipe gesture that lands within a graphical user interface region that displays the digital image). In addition to a swipe gesture (via a touch screen), a user input gesture can include various alternative user interactions, such as click and / or drag events, press events, multi-finger swipe events, and / or pinch events (e.g., via a mouse). A user input gesture can also include non-contact gestures or events (e.g., movement above a touch screen or movement captured by a digital camera).

[0041] As mentioned above, a digital image enhancement system can determine that a user input gesture includes movement in one or more directions (e.g., dimensions). As used herein, "movement" refers to a change, difference, or distance between two positions. In particular, the movement of a user input gesture includes the change, difference, or distance between a start position and an end position. A single user input gesture can include multiple movements relative to different directions (or dimensions). For example, a diagonal swipe gesture includes a first movement in a first (e.g., horizontal) direction and a second movement in a second (e.g., vertical) direction.

[0042] As used herein, the term "input mode" (or "mode") refers to a set of characteristics and / or parameters corresponding to a user selection and / or a user input gesture. For example, an input mode can indicate the characteristics (e.g., objects or colors) to be analyzed within a user-selected region. Similarly, an input mode can indicate one or more parameters corresponding to one or more movement directions in a user input gesture. For example, an input mode can indicate that a hue parameter corresponds to a first (horizontal) direction and a saturation parameter corresponds to a second (vertical) direction.

[0043] Additional details will now be provided with respect to illustrative diagrams depicting example embodiments and implementations of a digital image enhancement system. For example, Figure 1 FIG. shows a schematic diagram of an environment 100 for implementing a digital image enhancement system 110 in accordance with one or more embodiments. As shown, the environment 100 includes (a plurality of) server devices 102 connected to a plurality of client devices 104a - 104n via a network 106 (examples of which will be described in more detail below with reference to Figure 15 ).

[0044] As shown, the environment 100 can include (a plurality of) server devices 102. The (a plurality of) server devices 102 can generate, store, receive, and transmit various types of data, including digital images and enhanced digital images. For example, the (a plurality of) server devices 102 can receive data from a client device such as client device 104a and send the data to another client device such as client devices 104b, 104c, and / or 104n. The (a plurality of) server devices 102 can also transmit electronic messages between one or more users of the environment 100. In one example embodiment, the (a plurality of) server devices 102 are data servers. The (a plurality of) server devices 102 can also include communication servers or web hosting servers. Additional details regarding the (a plurality of) server devices 102 will be discussed below with respect to Figure 15 .

[0045] As shown, in one or more embodiments, the server device(s) 102 may implement all or a portion of the digital media management system 108 and / or the digital image enhancement system 110. The digital media management system 108 may collect, store, manage, modify, analyze, and / or distribute digital media. For example, the digital media management system 108 may receive digital media from the client devices 104a - 104n, store the digital media, edit the digital media, and provide the digital media to the client devices 104a - 104n.

[0046] The digital media management system 108 and / or the digital image enhancement system 110 may include the application(s) running on the server device(s) 102, or a portion may be downloaded from the server device(s) 102. For example, the digital image enhancement system 110 may include a web hosting application that allows the client devices 104a - 104n to interact with the content hosted at the server device(s) 102. By way of illustration, in one or more embodiments of the environment 100, one or more client devices 104a - 104n may access a web page supported by the server device(s) 102. In particular, the client device 104a may run a web application (such as a web browser) to allow a user to access, view, and / or interact with the web page or website hosted at the server device(s) 102.

[0047] To provide an illustrative example, in one or more embodiments, the client device 104a captures a digital image and transmits the digital image to the server device(s) 102. The digital media management system 108 may store the digital image (via the server device(s)). Additionally, the digital image enhancement system 110 may provide a digital image enhancement user interface for display via the client device 104a. The digital image enhancement system 110 may identify user interactions including selections and user input gestures (via the client device 104a). In response, the digital image enhancement system 110 may determine a modification to the digital image parameters, generate an enhanced digital image by applying the modification to the digital image parameters, and provide the enhanced digital image for display (via the client device 104a).

[0048] As just described, the digital image enhancement system 110 can be implemented, in whole or in part, by the respective elements 102-106 of the environment 100. It will be understood that although certain components or functions of the digital image enhancement system 110 have been described in the previous examples with respect to specific elements of the environment 100, various alternative implementations are possible. For example, in one or more embodiments, the digital image enhancement system 110 is implemented, in whole or in part, on the client device 104a. Similarly, in one or more embodiments, the digital image enhancement system 110 can be implemented on the server device(s) 102. Additionally, different components and functions of the digital image enhancement system 110 can be implemented separately among the client devices 104a-104n, the server device(s) 102, and the network 106.

[0049] Although Figure 1 The illustration shows a particular arrangement of the client devices 104a-104n, the network 106, and the server device(s) 102, but various additional arrangements are possible. For example, the client devices 104a-104n can communicate directly with the server device(s) 102 bypassing the network 106, or alternatively, the client devices 104a-104n can communicate directly with each other. Similarly, although Figure 1 the environment 100 can be depicted as having various components, the environment 100 can have additional or alternative components.

[0050] As mentioned above, the digital image enhancement system 110 can utilize context-aware sensors and / or multi-dimensional user input gestures to generate enhanced digital images. Figure 2 The illustration shows an overview of generating an enhanced digital image according to one or more embodiments. In particular, Figure 2 The illustration shows the digital image enhancement system 110 performing a series of actions 202-208.

[0051] Specifically, with respect to Figure 2 , the digital image enhancement system 110 performs the action 202 of identifying a user selection of a first location. For example, as discussed above, the digital image enhancement system 110 can provide a display of a digital image and a transparent sensor (i.e., a transparent sensor that appears on the digital image) via a digital image enhancement user interface. The digital image enhancement system 110 can monitor user interactions with the digital image enhancement user interface (e.g., the movement of a mouse or the movement of a finger on a touch screen) and modify the position of the transparent sensor. As the sensor moves, the digital image enhancement system 110 can analyze the sensor position on the digital image.

[0052] For example, the user may drag a finger to a first position and apply a long touch gesture to activate a sensor at the first position (e.g., based on the user moving a transparent sensor to the sensor position and applying a long touch gesture). By way of illustration, the digital image enhancement system 110 may perform operation 202 by detecting the movement of the transparent sensor to the first position (e.g., the user dragging a finger to the first position) and then a long tap, long press, or force touch event at the first position. Alternatively, the digital image enhancement system 110 may perform operation 202 by detecting a down touch of a user input (e.g., finger, mouse, or stylus) at a first position on the digital image.

[0053] As Figure 2 illustrated, operation 202 may also include detecting features of the digital image at the first position. For example, the digital image enhancement system 110 may apply a color analysis model and / or an object identification model to the sensor position. By way of illustration, in some embodiments, the digital image enhancement system 110 identifies a region of the digital image based on the transparent sensor (e.g., a window surrounded by the transparent sensor) and analyzes the region of the digital image to identify features such as objects or colors depicted in the region. Additional details regarding identifying digital image features using a sensor are provided below (e.g., with respect to Figure 3 ). Based on the one or more detected features, the digital image enhancement system 110 may identify one or more parameters to modify, as described in more detail below.

[0054] When performing operation 202, the digital image enhancement system 110 may also perform operation 204 of detecting a user input gesture including movement. For example, the digital image enhancement system may detect a user input gesture including movement from an initial position to a subsequent position. For example, as mentioned above, the user input gesture may include a press event at the initial position and a drag event (along a path) to a subsequent position. As Figure 2 shown, the user input gesture is provided on the digital image within the enhanced user interface. Thus, as discussed above, the digital image enhancement system 110 does not need to provide a visual element for receiving the user input gesture. Instead, with respect to Figure 2 , the digital image enhancement system 110 receives the user input gesture with respect to different positions within the digital image enhancement user interface where the digital image is displayed.

[0055] As shown, the user input gesture may include movement(s) in one or more directions. For example, the digital image enhancement system 110 may detect movement in the horizontal direction. The digital image enhancement system 110 may also detect a diagonal user input gesture and decompose the diagonal user input gesture into a first movement in the horizontal direction and a second movement in the vertical direction. Additional details regarding analyzing the user input gesture to identify movement and corresponding directions are provided below (e.g., regarding Figure 4 ).

[0056] As Figure 2 shown, the digital image enhancement system 110 also performs an action 206 that determines the modification to be made based on the user input gesture. For example, the digital image enhancement system 110 may determine a modification to a parameter based on the movement(s) and corresponding direction(s) detected from the action 204. For example, the digital image enhancement system 110 may determine a modification to a first parameter of the digital image based on the first movement in the horizontal direction. Additionally, the digital image enhancement system 110 may determine a modification to a second parameter of the digital image based on the second movement in the vertical direction. Thus, the digital image enhancement system 110 may determine modified parameter values for different parameters based on movement in different directions.

[0057] In some embodiments, the magnitude of the modification (e.g., the magnitude of the change to the parameter value) is based on the relative displacement of the movement in a particular direction. For example, the digital image enhancement system 110 may identify the horizontal distance between the initial position of the movement and the subsequent position of the movement and modify the parameter value of the first parameter in proportion to the horizontal distance. In some embodiments, the magnitude of the modification is based on the absolute position within the digital enhancement user interface. For example, the digital image enhancement system 110 may map the coordinates of the digital enhancement user interface to parameter values, detect the final position of the movement, and identify the parameter value based on the mapping and coordinates of that final position. Additional details regarding determining parameter values based on movement are provided below (e.g., regarding Figure 4 ).

[0058] As shown, operation 206 may also include determining a modification based on features of the digital image at the sensor location. In fact, in some embodiments, the digital image enhancement system 110 determines the parameters to be modified based on features of the digital image at the sensor location. For example, the digital image enhancement system 110 may identify the hue, saturation, and / or brightness (from operation 202) at the sensor location. In response, the digital image enhancement system 110 may select a modification to the corresponding hue, saturation, and / or brightness. By way of illustration, upon detecting blue at the sensor location, the digital image enhancement system 110 may determine a first modification to the saturation parameter of the blue within the digital image. Additionally, the digital image enhancement system 110 may determine a modification to the hue parameter of the blue within the digital image.

[0059] Having identified the parameters to be modified (based on the features at the sensor location), the digital image enhancement system 110 may determine the magnitude of the parameter values based on the user input gesture. For example, continuing the previous example, the digital image enhancement system 110 may identify the modified saturation value for the blue within the digital image based on movement in the horizontal direction. Additionally, the digital image enhancement system 110 may identify the modified hue value for the blue within the digital image based on movement in the vertical direction. In this manner, the digital image enhancement system 110 may determine the modification of the parameters based on the features at the sensor location and the direction of movement on the digital image in the digital image enhancement user interface. Additional details regarding identifying parameters and parameter values based on the sensor and user input gestures are provided below (e.g., regarding Figures 5 - 8 ).

[0060] In some embodiments, the digital image enhancement system 110 may also select features and / or parameters for analysis and / or modification based on the input mode. For example, the digital image enhancement system 110 may utilize multiple input modes to select the specific features to target and / or the parameters to modify. For example, the digital image enhancement system 110 may utilize a first mode that detects the brightness at the sensor location and modifies the brightness (based on movement in the horizontal direction) and saturation (based on movement in the vertical direction). Similarly, the digital image enhancement system 110 may utilize a second mode that detects the color at the sensor location and modifies the saturation (based on movement in the horizontal direction) and hue (based on movement in the vertical direction). Additional details regarding the different modes are provided below (e.g., regarding Figure 8 ).

[0061] As Figure 2As shown, based on determining the modifications to be made (e.g., the parameters to be modified and the corresponding parameter values), the digital image enhancement system 110 may perform the action 208 of generating an enhanced digital image. In particular, the digital image enhancement system 110 may generate and provide the enhanced digital image for display via the digital image enhancement user interface. By modifying the digital image according to the parameters and parameter values determined at action 206, the digital image enhancement system 110 may perform action 208. For example, based on detecting blue, horizontal movement, and vertical movement at the sensor location, the digital image enhancement system 110 may modify the color of the blue pixels in the digital image to purple (i.e., modify any pixel falling within the threshold hue range of blue to purple), and increase the saturation of the blue pixels. Additional examples of generating an enhanced digital image within the digital image enhancement user interface are provided below (e.g., regarding Figures 9A - 11 ).

[0062] The actions described herein (and regarding Figure 2 ) are intended to be illustrative and are not intended to limit potential embodiments. Alternative embodiments may include more, fewer, or different actions than those Figure 2 clarified or illustrated. For example, in some embodiments, prior to action 202, the digital image enhancement system 110 applies a digital image correction algorithm. By way of illustration, the digital image enhancement system 110 may apply a digital image correction algorithm to automatically modify certain parameters (e.g., brighten a dark image). The digital image enhancement system 110 may then continue to modify the digital image by performing actions 202-208.

[0063] In addition, the digital image enhancement system 110 may also select parameters based on applying the digital image correction algorithm. By way of illustration, the digital image enhancement system 110 may apply a digital image correction algorithm that automatically adjusts parameters (e.g., to mimic a "professional" digital image appearance). The digital image enhancement system 110 may identify (or rank) the parameter changes resulting from applying the digital image correction algorithm. For example, the digital image enhancement system 110 may rank the parameters based on the percentage or value of the change. The digital image enhancement system 110 may utilize the parameter changes from applying the digital image correction algorithm to select parameters corresponding to movement in various directions. For example, based on the ranked parameters from applying the digital image correction algorithm, the digital image enhancement system 110 may map the first parameter (e.g., the highest ranked parameter) to the horizontal direction, and the second parameter (e.g., the second ranked parameter) to the vertical direction.

[0064] The digital image enhancement system 110 may also select parameters based on various other factors. For example, the digital image enhancement system 110 may select parameters based on the content of the digital image or historical usage. By way of illustration, the digital image enhancement system 110 may select parameters based on usage frequency (e.g., the parameters most frequently used among one or more users). The digital image enhancement system 110 may also select parameters based on detected objects (e.g., modifying the brightness parameter when a flower is detected).

[0065] Similarly, although many of the embodiments described with respect to Figure 2 indicate modifying two parameters based on movement in two directions, the digital image enhancement system 110 may also modify additional parameters based on movement in different directions (or modify a single parameter based on movement in a single direction). For example, in some embodiments, the digital image enhancement system 110 may map four different directions to four different styles or filters. The digital image enhancement system 110 may modify the parameters corresponding to the four different styles or filters based on movement corresponding to the four different directions. Additional details regarding modifying style / filter parameters are provided below (e.g., with respect to Figure 7 ).

[0066] In addition, the actions described herein may be performed in a different order, may be repeated or performed in parallel with each other, or may be performed in parallel with different instances of the same or similar steps / actions. For example, in some embodiments, actions 204 - 208 may be iteratively repeated when the user performs different movements. For example, the digital image enhancement system 110 may dynamically generate a first enhanced digital image based on movement to one location and may generate an additional enhanced digital image based on additional movement to an additional location. In this way, the digital image enhancement system 110 may provide the user with real-time dynamic feedback regarding how the modifications and movements affect the visual appearance of the digital image.

[0067] Similarly, the digital image enhancement system 110 may also repeat actions 202 - 208 with respect to different sensor locations, different features, and / or different parameters. For example, the digital image enhancement system 110 may identify an additional sensor location selected by the user, determine additional features at the additional sensor location, identify an additional user input gesture, and modify additional parameters (based on the additional features and the additional user input gesture) to generate an additional enhanced digital image.

[0068] As discussed above, in some embodiments, the digital image enhancement system 110 utilizes sensors to identify features at a selected location of a digital image. Figure 3 Illustrates identifying digital image features using sensors according to one or more embodiments. Specifically, Figure 3The figure shows a computing device 302 having a touch screen depicting a digital image enhancement user interface 304. In particular, the digital image enhancement user interface 304 depicts a digital image (i.e., an image of a leaf) and a transparent sensor 306.

[0069] As Figure 3 illustrated, the digital image enhancement system 110 provides the transparent sensor 306 for display based on user interaction with the digital image enhancement user interface 304. In particular, when the user moves a finger on the touch screen, the digital image enhancement system 110 modifies the position of the transparent sensor 306. In response to the selection of a particular position, the digital image enhancement system 110 can use the transparent sensor 306 to identify the underlying content of the digital image.

[0070] For example, as Figure 3 shown, the user selects the position 306a of the transparent sensor 306. In response, the digital image enhancement system 110 identifies the digital image content 308. In particular, the digital image enhancement system 110 identifies the region of the digital image corresponding to the transparent sensor 306 (e.g., the region surrounded by the transparent sensor 306). The digital image enhancement system 110 identifies the digital image content by isolating the digital image based on the region corresponding to the transparent sensor 306. Thus, the digital image enhancement system 110 can use the transparent sensor 306 as a sampling window to identify the digital content.

[0071] Once the digital image content 308 is identified, the digital image enhancement system 110 analyzes the digital image content 308 to determine digital image features. As Figure 3 shown, the digital image enhancement system 110 can use a color analysis model 310 and / or an object identification model 314 to determine digital image features 312 and / or digital image features 316. In particular, the digital image enhancement system 110 can determine features such as color, brightness, saturation, object class, and / or object boundaries.

[0072] As illustrated, the digital image enhancement system 110 uses the color analysis model 310 to analyze the digital image content 308. The color analysis model 310 can include a variety of computer-implemented algorithms. For example, the color analysis model 310 can include a statistical model that determines color information about individual pixels and generates various statistical metrics. For example, the digital image enhancement system 110 can determine the color, brightness, and / or saturation of each pixel at position 306a and use the color analysis model 310 to determine the mean, median, mode, variance, range, standard deviation, or skewness of the color, brightness, and / or saturation. The digital image enhancement system 110 can use these metrics as digital image features 312.

[0073] As mentioned above, the digital image enhancement system 110 may also determine features as ranges. For example, the digital image enhancement system 110 may determine a color range, a brightness range (e.g., a hue range), and / or a saturation range. By way of illustration, the digital image enhancement system 110 may utilize a color analysis model 310 to determine a hue region (e.g., shadows, highlights, and midtones) corresponding to a first region. For example, the digital image enhancement system 110 may analyze the pixels of the digital image content 308 and determine a measure of the frequency of a particular hue (e.g., a histogram of pixel hues). The digital image enhancement system 110 may then determine whether the pixels in the digital image content 308 correspond to a particular hue region. For example, if a threshold number or percentile of the pixels falls within a first range of hues (e.g., the lower third), the digital image enhancement system 110 may determine a shadow hue region. Similarly, if a threshold number or percentile of the pixels falls within a second range of hues (e.g., the upper third), the digital image enhancement system 110 may identify a highlight hue region. Similarly, if a threshold number or percentile of the pixels falls within a third range of hues (e.g., the middle third), the digital image enhancement system 110 may identify a midtone region.

[0074] In some embodiments, the color analysis model 310 includes a machine learning model (such as a neural network). For example, the color analysis model 310 may include a convolutional neural network that classifies the digital image content 308 to generate digital image features 312. By way of illustration, the digital image enhancement system 110 may utilize a neural network classifier to determine the dominant color, brightness, or saturation of the digital image content 308.

[0075] As shown, the digital image enhancement system 110 may also utilize an object identification model 314 to generate digital image features 316. For example, the digital image enhancement system 110 may utilize the object identification model 314 to identify object boundaries and / or object classes based on the digital image content 308.

[0076] The object identification model 314 may include various computer-implemented algorithms. For example, in some embodiments, the object identification model 314 includes a statistical object identifier. For example, in some embodiments, the object identification model 314 identifies an object based on a statistical color profile corresponding to a particular object. By way of illustration, leaves tend to have a particular color profile (e.g., a standard deviation of color and an average color). The digital image enhancement system 110 may detect the standard deviation and average color of the colors within the digital image content 308, compare the average color and standard deviation to the leaf color profile, and determine that the digital image content 308 depicts a leaf.

[0077] In some embodiments, the object identification model 314 includes one or more machine learning models (e.g., one or more neural networks). For example, the object identification model 314 can include a neural network classifier, such as a convolutional neural network. The digital image enhancement system 110 can utilize the (multiple) neural networks to determine object classes and / or object boundaries (e.g., object classification and segmentation). For illustration, in some embodiments, the digital image enhancement system 110 utilizes the YOLO (You-Only-Look-Once) object detection algorithm.

[0078] Although Figure 3 The use of the color analysis model 310 and the object identification model 314 to determine specific digital image features has been described, but the digital image enhancement system 110 can utilize various models to identify various digital image features. For example, in some embodiments, the digital image enhancement system 110 can utilize a geographic location model and / or a time classification model to generate features including time (e.g., season, time of day, time of year, or date) and geographic location.

[0079] The color analysis model 310 and / or the object identification model 314 can detect, utilize, and / or generate various features. For example, the model can detect shape elements, such as line segments and edges with various thicknesses and orientations. As mentioned, the color analysis model 310 can utilize a convolutional neural network architecture (e.g., a deep learning network) to capture relevant local image content near the sensor. For example, in some embodiments, the digital image enhancement system 110 utilizes a pre-trained neural network. A network trained to recognize objects or reproduce images (e.g., an autoencoder) can be used. For this purpose, the trained network can be frozen, and various hidden neuron activations can be used to represent one or more features of interest. For example, a feature that responds to such an image content of green with leaf texture can drive changes in parameters associated with the leaves, such as changing the green hue and changing the medium spatial frequency content, thereby controlling the sharpness of the leaves without exacerbating noise.

[0080] In addition, although Figure 3 The transparent sensor 306 is illustrated in the form of a transparent circle, but the digital image enhancement system 110 can utilize sensors in various different visual forms. For example, the digital image enhancement system 110 can utilize an opaque sensor. In addition, the digital image enhancement system 110 can utilize sensors with different shapes, such as squares, ellipses, rectangles, triangles, or user-defined polygons.

[0081] In addition, even Figure 3The figure shows digital image content 308 that matches the area covered by sensor 306. The digital image enhancement system 110 can also analyze digital image content that is not aligned with the area of sensor 306. For example, in some embodiments, the digital image content 308 is smaller than the area of sensor 306, and in some embodiments, the digital image content 308 is larger than the area of sensor 306 (e.g., twice the size of the sensor).

[0082] In some embodiments, the digital image enhancement system 110 can analyze a larger portion (or even the entire digital image) to determine features that fall within the location of the sensor. For example, to determine that a first location includes an object, the digital image enhancement system 110 can analyze the entire digital image, identify the objects in the digital image, and determine whether the first location depicts a portion of one of the identified objects. By way of illustration, with respect to Figure 3 , to determine that the location 306a of sensor 306 includes a depiction of a leaf, the digital image enhancement system 110 can apply the object identification model 314 to a larger portion (e.g., the entire digital image) of the digital image. The digital image enhancement system 110 can use the object identification model 314 to identify the leaves in the digital image and then determine that the location 306a overlaps with the identified leaves.

[0083] As mentioned above, the digital image enhancement system 110 can determine parameter values based on user input gestures that include movement in one or more directions. In particular, in some embodiments, the digital image enhancement system 110 identifies a relative displacement (the relative change between an initial position and a subsequent position) and determines a proportional change in the parameter values based on that relative displacement. In some embodiments, the digital image enhancement system 110 identifies movement to a location and determines parameter values based on the absolute position of that location within the user interface (i.e., not relative to the starting position). For example, Figure 4 The figure shows identifying parameter values from a user input gesture based on the relative displacement and absolute position of a moving location according to one or more embodiments.

[0084] Specifically, Figure 4The figure shows a user input gesture (e.g., a press-and-drag gesture) on a computing device 402 having a display screen 404, where the user input gesture includes a movement 406 between an initial position 408a and a subsequent position 408b. As illustrated, in some embodiments, the digital image enhancement system 110 determines that the movement 406 includes a horizontal change 410 (i.e., a movement in the horizontal direction) and a vertical change 412 (i.e., a movement in the vertical direction). Based on the horizontal change 410, the digital image enhancement system 110 determines a corresponding (i.e., proportional) change in hue. Additionally, based on the vertical change 412, the digital image enhancement system 110 determines a corresponding (i.e., proportional) change in saturation. Thus, the change in the parameter value is proportional to the horizontal and vertical movements relative to the initial position 408a. Thus, Figure 4 the illustrated embodiment shows that the digital image enhancement system 110 can modify two parameters in response to a single user input gesture (e.g., a diagonal touch gesture).

[0085] As Figure 4 illustrated, in some embodiments, the digital image enhancement system 110 determines that the subsequent position 408b includes a horizontal coordinate 414 and a vertical coordinate 416 relative to a global coordinate system. In particular, the horizontal coordinate 414 reflects the horizontal distance from the origin of the global coordinate system, and the vertical coordinate 416 reflects the vertical distance from the origin. The digital image enhancement system 110 maps the coordinates of the global coordinate system (e.g., absolute position) to a corresponding range of parameter values. Thus, the digital image enhancement system 110 maps the position to a corresponding parameter value (e.g., a vertical position has a corresponding hue value in the range of 0 - 360, while a horizontal position has a corresponding saturation value in the range of 0 - 100). As shown, the digital image enhancement system 110 uses the vertical coordinate 416 to determine the saturation value (e.g., 91) and uses the horizontal coordinate 418 to determine the hue value (e.g., 291).

[0086] Although Figure 4 the figure shows specific parameter types (e.g., hue and saturation), the digital image enhancement system 110 can determine parameter values for any parameter described herein. Additionally, although Figure 4 the lower left corner of the display screen is used as the origin of the Cartesian coordinate system, the digital image enhancement system 110 can use various different coordinate systems (e.g., polar coordinates) and various different origins (e.g., origins based on different positions of the display screen, user interface, digital image, or elements within the user interface).

[0087] Additionally, although Figure 4The figure shows a single user input gesture having a horizontal component and a vertical component. However, in alternative embodiments, the digital image enhancement system 110 may detect a first user input gesture in a first direction (e.g., the horizontal direction) and a second user input gesture in a second direction (e.g., the vertical direction). In other words, the digital image enhancement system 110 may map a single user input gesture to a single direction. For example, the digital image enhancement system 110 may detect that a first user input gesture is within a threshold in a first direction (e.g., horizontal or vertical), and map the first user input gesture to the first direction - even if the first user input gesture has a component in a direction other than the first direction. Thus, the digital image enhancement system 110 may modify a single parameter in response to a single user input gesture, or modify multiple parameters multiple times in response to multiple separate user input gestures.

[0088] As mentioned above, in some embodiments, the digital image enhancement system 110 may select different parameters to modify based on features detected at the sensor locations. Figure 5 The figure shows determining various parameters to be modified based on different features (e.g., hue regions) detected at different sensor locations of a digital image, according to one or more embodiments. For example, Figure 5 The figure shows a computing device 500 displaying a digital image 502. Figure 5 Also shown are a first sensor location 504a, a second sensor location 504b, and a third sensor location 504c with respect to the digital image 502. For each of the sensor locations 504a - 504c, the digital image enhancement system 110 determines different parameters to be modified based on detecting varying features of the digital image 502.

[0089] For example, with respect to the first sensor location 504a, the digital image enhancement system 110 detects that the digital content at the first sensor location 504a corresponds to a first feature 506a (i.e., the digital content at the first sensor location corresponds to midtones). In response, the digital image enhancement system 110 may select a first parameter 508 (i.e., exposure) and a second parameter 510 (i.e., contrast). Additionally, the digital image enhancement system 110 may map the parameters to different directions (e.g., exposure corresponds to movement in the horizontal direction, while contrast corresponds to movement in the vertical direction).

[0090] Additionally, at the second sensor position 504b, the digital image enhancement system 110 detects a second feature 506b. In particular, the digital image enhancement system 110 detects that the digital content at the second sensor position 504b corresponds to a shadow tone. In response, the digital image enhancement system 110 may select a third parameter 512 (shadow brightness) and a fourth parameter 514 (black clip point). Additionally, the digital image enhancement system 110 may map the parameters to a direction of movement (e.g., shadow brightness is mapped to the horizontal direction, while the black clip point is mapped to the vertical direction).

[0091] Furthermore, at the third sensor position 504c, the digital image enhancement system 110 detects a third feature 506c. In particular, the digital image enhancement system 110 determines that the digital content at the third sensor position 504c corresponds to a highlight tone. In response, the digital image enhancement system 110 may select a fifth parameter 516 (highlight brightness) and a sixth parameter 518 (white clip point) having corresponding directions (i.e., horizontal and vertical respectively).

[0092] Thus, the digital image enhancement system 110 may select various different parameters based on detecting different features at different sensor positions. Although Figure 5 the figures illustrate the digital image enhancement system 110 selecting specific parameters in response to detecting a specific feature, the digital image enhancement system 110 may select multiple different parameters in response to detecting multiple different features. For example, in response to detecting orange, the digital image enhancement system 110 may select an orange brightness parameter (which defines and / or modifies the brightness of orange in the digital image) and an orange hue parameter (which defines and / or modifies the hue of orange in the digital image). Additionally, in some embodiments, the digital image enhancement system 110 selects parameters without detecting features of the digital image. For example, in some embodiments, such as in response to a user selection of a parameter to be modified, the digital image enhancement system 110 selects a contrast parameter independently of any feature of the digital image.

[0093] As discussed above, the digital image enhancement system 110 may determine modifications based on features (detected at sensor positions) and user input gestures on the digital image in multiple directions. For example, when mapping a parameter to a specific direction of movement, the digital image enhancement system 110 may then monitor the user input gesture and modify the parameter value based on the user input gesture. In this way, the digital image enhancement system 110 may efficiently and accurately generate digital image enhancements that would conventionally require modifying various user interface control tools. For example, Figure 6 the figures illustrate generating modifications (and corresponding changes to sliders or other conventional user interface tools for the same modifications) based on features and user input gestures according to one or more embodiments of the digital image enhancement system 110.

[0094] For example, in Figure 6 , the digital image enhancement system 110 detects that the sensor position of the digital image includes green in the midtone range of the intensity values (e.g., the "midtone" feature). The digital image enhancement system 110 selects a midtone brightness parameter and maps the midtone brightness parameter to a movement in the horizontal direction. Additionally, the digital image enhancement system 110 detects a user input gesture including a horizontal movement. In response, the digital image enhancement system 110 modifies the midtone brightness proportionally to the magnitude of the horizontal movement.

[0095] As shown, modifying the midtone brightness of the image according to this example is related to the modification of other user visual parameter value modification elements or multiple sliders. For example, moving the exposure slider will brighten the image, but this will affect not only the midtones but also the entire tonal range. Therefore, this modification may also involve moving the shadow slider and the highlight slider to affect the midtones.

[0096] In addition, modifying the brightness within a specific tonal range may also include modifying the color curve. The color curve (as shown in Figure 6 ) includes a visual representation of the remapping of the image tones. The color curve can be expressed as a function of the input level to the output level. For example, by modifying this function within certain tonal ranges, the user can interact with the color curve to modify the function. The user can modify various variables for the color curve, such as: adding, moving, or removing points that define the color curve, modifying the range of the tonal regions in the color curve, or modifying the intensity within a specific tonal range. The digital image enhancement system 110 can make intuitive modifications to the variables of the color curve without confusing the user by presenting the color curve for display.

[0097] In fact, the digital image enhancement system 110 can utilize the gesture input on the digital image to make the modifications illustrated in Figure 6 . In fact, by determining a specific parameter (midtone brightness) based on the features of the digital image itself, the digital image enhancement system 110 can control and modify the relevant parameters to accurately modify the digital image without repeated user interaction with various different sliders and visual elements.

[0098] Although Figures 5 - 6 describes selecting parameters based on detected different tonal regions (i.e., different brightness features), as mentioned above, the digital image enhancement system 110 can select parameters based on any of the features described herein. For example, the digital image enhancement system 110 can select parameters based on the objects detected in the digital image (e.g., selecting the saturation parameter when a flower is detected). Similarly, as mentioned above (regarding Figure 2) In some embodiments, the digital image enhancement system 110 selects parameters based on the application of digital image correction algorithms.

[0099] As mentioned above, in some embodiments, the digital image enhancement system 110 may modify the parameters of a digital image by mixing styles or filters based on user input gestures on the digital image. For example, Figure 7 FIG. shows a computing device 700 having a digital image enhancement user interface 702. The digital image enhancement system 110 may associate regions, positions, and / or orientations of the digital image enhancement user interface 702 with four styles 704 - 710. Each style has its own mixture of individual parameters. For example, style 704 may include a style defined by the user. Similarly, styles 706 - 710 may include system-predefined filters. Based on user interaction, the digital image enhancement system 110 may mix the parameters of the four styles 704 - 710.

[0100] For example, in one or more embodiments, the digital image enhancement system 110 performs weighted mixing (e.g., distance-weighted mixing) based on a decreasing function of the distance from each style. Thus, since the user input gesture is closer to a corner, the digital image enhancement system 110 may emphasize the style corresponding to that corner. When the user input gesture is equidistant from the four corners corresponding to the styles, the digital image enhancement system 110 may equally mix the parameters of the individual styles.

[0101] In some embodiments, the digital image enhancement system 110 may use a mixed color lookup table to mix parameters from different styles. For example, the digital image enhancement system 110 may determine a mixed color lookup table by mixing the color outputs for any specified input color. For example, the digital image enhancement system 110 may generate a lookup table for each of styles 704 - 710, where each lookup table identifies the output color corresponding to an input color from the digital image. The digital image enhancement system 110 may obtain the output colors from each lookup table for each style to create a mixed color lookup table. The digital image enhancement system 110 may utilize the mixed color lookup table to identify the mixed color from the input color.

[0102] In some embodiments, the digital image enhancement system 110 utilizes a zero style at the central region of the digital image. Thus, when the user's finger is in the central region, the digital image enhancement system 110 does not apply any of styles 704 - 710. In other embodiments, the digital image enhancement system 110 includes an auto-correction element at the central region of the digital image. In such embodiments, when the user's finger is in the central region, the digital image enhancement system 110 applies a digital image correction algorithm (instead of one of the four styles).

[0103] Although Figure 7 The figure shows four styles 704-710 having corresponding regions at the corners of the digital image enhancement user interface. However, the digital image enhancement system 110 may utilize a different number of styles with different corresponding positions. For example, instead of mixing four styles, the digital image enhancement system 110 may mix two styles and associate the two styles with different positions or orientations (e.g., the top and bottom of the screen or positions along the screen edge). For illustration, the digital image enhancement system 110 may associate the style positions along the digital image boundary inside or outside the digital image. Additionally, in some embodiments, instead of associating the styles with corners, the digital image enhancement system 110 associates a first blending weight of a first style with a first (horizontal) movement direction and a second blending weight of a second style with a second (vertical) movement direction.

[0104] As mentioned above, the digital image enhancement system 110 may also utilize various input modes to assist in selecting specific features and / or parameters. For example, Figure 8 The figure shows input modes 802-810 utilized by the digital image enhancement system 110 according to one or more embodiments. The digital image enhancement system 110 may select and apply the input modes 802-810 when generating the enhanced digital image. For example, in response to a mode selection user input, the digital image enhancement system 110 may select the first mode 802, then search for features corresponding to the feature type corresponding to the first mode and modify the parameters corresponding to the first mode.

[0105] For example, as illustrated, the first mode 802 is associated with a feature type 802a (i.e., a color or hue feature). Additionally, the first mode 802 is associated with parameters 802b-802c. In particular, the first mode 802 is associated with a first parameter 802b (i.e., saturation) corresponding to a first direction (i.e., the horizontal direction). Furthermore, the first mode 802 is associated with a second parameter 802c (i.e., hue) corresponding to a second direction (i.e., the vertical direction). Thus, when the first mode 802 is selected, the digital image enhancement system 110 may analyze the sensor positions for color and modify the saturation based on a user input gesture including movement in the horizontal direction, and modify the hue based on a user input gesture including movement in the vertical direction.

[0106] In some embodiments, the digital image enhancement system 110 changes parameters 802b, 802c based on detected specific features. For example, when utilizing the first mode 802, the digital image enhancement system 110 may detect green as the color at the sensor location. In response, the digital image enhancement system 110 may utilize the first parameter 802b, but a more specific version of the first parameter 802b that modifies green saturation. Thus, although the first mode 802 corresponds to specific parameters, the digital image enhancement system 110 may apply the parameters based on features detected within the digital image.

[0107] As Figure 8 shown, the digital image enhancement system 110 may also utilize a second mode 804. As Figure 8 shown, the second mode 804 may include a feature type 804a (i.e., a color feature), a first parameter 804b (i.e., brightness) corresponding to a first direction (i.e., the horizontal direction), and a second parameter 804c corresponding to a second direction (i.e., the vertical direction). Thus, when applying the input mode 804, the digital image enhancement system 110 may analyze the sensor location for color and then modify the brightness (in response to movement in the horizontal direction) and modify the saturation (in response to movement in the vertical direction).

[0108] As Figure 8 further illustrated, the digital image enhancement system 110 may utilize a third mode 806 associated with a feature type 806a (i.e., a hue region feature) and a parameter 806b (i.e., a color parameter curve variable). As discussed above (e.g., with respect to Figure 6 ), the digital image enhancement system 110 may utilize a color curve to modify the digital image. For example, the digital image enhancement system 110 may modify the intensity values within the hue region of the color curve. Similarly, the digital image enhancement system 110 may modify the boundaries or cut-off points between the hue regions within the color curve. The digital image enhancement system 110 may utilize these variables as the parameter 806b. For example, the digital image enhancement system 110 may modify the intensity (or height) of the color curve based on movement in a first direction. Additionally, the digital image enhancement system 110 may modify the boundary of the hue region (or the horizontal position of a point on the color curve) based on movement in a second direction.

[0109] As Figure 8As shown, the digital image enhancement system 110 may also include a fourth mode 808 (i.e., the structure mode) associated with a feature type 808a (i.e., the detected object), a first parameter 808b (i.e., saturation), and a second parameter 808c (i.e., hue). Thus, when implementing the fourth mode 808, the digital image enhancement system 110 may identify the objects depicted in the sensor location, modify the saturation of the objects (and / or similar objects of the same class) in response to movement in the horizontal direction, and modify the hue of the objects (and / or similar objects of the same class) in response to movement in the vertical direction.

[0110] In addition, Figure 8 it is shown that the digital image enhancement system 110 may also apply other modes 810. For example, the digital image enhancement system 110 may define various modes based on different combinations of the features and parameters described herein. By way of illustration, the digital image enhancement system 110 may utilize a mode that detects features including both color and saturation and modifies hue and saturation (or hue and brightness or hue and contrast). Similarly, the digital image enhancement system 110 may utilize a style input mode that modifies a preset style (as described with respect to Figure 7 ). In addition, although Figure 8 the figures illustrate various input modes with predetermined feature types to be analyzed, in some embodiments, the digital image enhancement system 110 utilizes an input mode that does not specify (or analyze) a feature type (i.e., the input mode only specifies parameters).

[0111] In one or more embodiments, the digital image enhancement system 110 selects or determines the mode to be applied (e.g., from modes 802 - 810). The digital image enhancement system 110 may select the mode based on a variety of factors. For example, in some embodiments, the digital image enhancement system 110 selects the mode based on user input. For example, the digital image enhancement system 110 may detect a mode selection user input that indicates a user selection of a particular node. By way of illustration, in some embodiments, the digital image enhancement system 110 switches between input modes based on a double - click or double - tap event.

[0112] The digital image enhancement system 110 may also select the input mode based on the digital image content. For example, the digital image enhancement system 110 may perform a preliminary analysis of the digital image to determine digital image features (e.g., color statistics, the objects depicted, the time of day, the season, or the location) and select the input mode based on the digital image features. For example, based on detecting a digital with a dark profile, the digital image enhancement system 110 may select a light mode. Similarly, based on detecting a digital image with little color variation, the digital image enhancement system 110 may select a color mode.

[0113] In some embodiments, the digital image enhancement system 110 may select an input mode based on applying a digital image correction algorithm. For example, the digital image enhancement system 110 may apply a digital image correction algorithm and determine a parameter that has changed (e.g., changed the most) relative to the original digital image. Then, the digital image enhancement system 110 may select a color mode corresponding to the changed parameter.

[0114] The digital image enhancement system 110 may also select an input mode based on historical usage. For example, the digital image enhancement system 110 may select an input made based on the last used input mode. Similarly, the digital image enhancement system 110 may select an input mode based on usage frequency (e.g., the input mode most commonly used by a particular user). In some embodiments, the digital image enhancement system 110 may select an input mode based on both the characteristics of the digital image and the usage history. For example, the digital image enhancement system 110 may detect an object in the digital image and determine that the user has previously modified the digital image with that object using a particular input mode. In response, the digital image enhancement system 110 may select a particular input mode.

[0115] As mentioned above, the digital image enhancement system 110 may utilize a digital image enhancement user interface to generate an enhanced digital image. Figures 9A - 10 The figure illustrates generating an enhanced digital image using a digital image enhancement user interface according to one or more embodiments. For example, Figure 9A The figure illustrates a computing device 900 having a touch screen 902 that displays a digital image enhancement user interface 904 including a digital image 906 (i.e., a digital image depicting a flower).

[0116] The digital image enhancement system 110 detects that the user drags a finger to a first position 908. The digital image enhancement system 110 provides a sensor 910 for display on the digital image enhancement user interface (as the user drags the finger). In some embodiments, when the user touches the display screen, the digital image enhancement system 110 increases the size of the sensor 910 (to make the position of the sensor easier to see at any given time). Additionally, as the digital image enhancement system 110 detects movement of the sensor 910 at different positions, the digital image enhancement system 110 may provide an indicator of the content at different positions (as well as a modification corresponding to the currently selected input mode). For example, as Figure 9A shown, the digital image enhancement system 110 provides a dynamic indicator 911 that indicates that the digital content at the current position includes "highlights", and the current input mode will modify the light within the highlights (e.g., brightness and contrast).

[0117] Specifically, as Figure 9AAs shown, sensor 910 is associated with an input mode. Specifically, sensor 910 displays a graphic (e.g., a circle with a brightness gradient) that indicates that the light input mode is selected. Based on the light input mode, digital image enhancement system 110 can detect a brightness feature at the first location 908. For example, digital image enhancement system 110 detects that the digital image 906 at the first location 908 includes pixels corresponding to highlights (e.g., within a highlight brightness category or range).

[0118] At the first location 908, digital image enhancement system 110 can detect a long press or other user input to activate the sensor or feature detector capabilities of digital image enhancement system 110. Digital image enhancement system 110 can detect one or more features of the digital image at the first location 908. In particular, digital image enhancement system 110 can identify parameters to modify those parameters and associate those parameters with a direction of movement. Since digital image enhancement system 110 is applying the light input mode, digital image enhancement system 110 can associate a brightness parameter (e.g., changing the brightness of the pixels depicting the highlights) with movement in the horizontal direction and a saturation parameter (e.g., changing the saturation of the pixels depicting the highlights) with movement in the vertical direction.

[0119] As Figure 9A As illustrated, digital image enhancement system 110 detects a user input gesture 912. Specifically, after selecting the first location 908, digital image enhancement system 110 detects a user input gesture that begins at the initial location 912a and ends at the subsequent location 912b. In one embodiment, based on the user input gesture 912, digital image enhancement system 110 can identify a first movement in the horizontal direction and a second movement in the vertical direction. Based on the first movement in the horizontal direction and the feature at the first location, digital image enhancement system 110 can modify the brightness. Specifically, digital image enhancement system 110 can modify the brightness of the pixels that fall within the highlight category or range. Based on the second movement in the vertical direction and the feature at the first location, digital image enhancement system 110 can also modify the saturation. In particular, digital image enhancement system 110 can modify the saturation of the pixels that fall within the highlight category or range. As discussed above, digital image enhancement system 110 can determine the magnitude of the brightness and saturation changes based on the magnitude of the horizontal movement and the magnitude of the vertical movement.

[0120] In another embodiment, digital image enhancement system 110 can determine that the user input gesture 912 is more horizontal than vertical or within a threshold angle of horizontal movement. In response, digital image enhancement system 110 can modify the brightness of the pixels that fall within the highlight category or range based on the magnitude of the first user input gesture 912.

[0121] After identifying the modifications to be made (e.g., the parameters to be changed and the parameter values), the digital image enhancement system 110 can generate an enhanced digital image. After detecting the user input gesture 912, the digital image enhancement system 110 can modify the parameters to generate the enhanced digital image 914. Specifically, the digital image enhancement system 110 can modify the brightness (and optionally the saturation) of the pixels in the highlight tone range. In addition, the digital image enhancement system 110 can provide the enhanced digital image 914 for display via the digital image enhancement user interface 904.

[0122] As mentioned, the digital image enhancement system 110 can utilize sensors to iteratively change different parameters. For example, Figure 9B The figure shows further modification of the enhanced digital image 914 using sensors and multi-dimensional gesture input. Specifically, regarding Figure 9B , the digital image enhancement system 110 identifies a movement to a new location 920 (e.g., a drag event). The digital image enhancement system 110 also identifies a user input indicating a change to a different input mode (e.g., a double-tap event). In response, the digital image enhancement system 110 can provide the sensor 910 for display at the new location 920. In addition, the digital image enhancement system 110 can provide new graphics within the sensor 910 indicating a different input mode (i.e., the color input mode).

[0123] Based on additional user input (e.g., a long-press event), the digital image enhancement system 110 can activate the sensor 910, determine the characteristics of the digital image at the new location 920, and search for or wait for a user input gesture. Since the digital image enhancement system 110 is applying the color input mode, the digital image enhancement system 110 can detect the color (i.e., magenta) at the first location. The digital image enhancement system 110 can also identify the parameters corresponding to the color input mode (e.g., hue for the horizontal direction and saturation for the vertical direction).

[0124] As Figure 9BAs shown, digital image enhancement system 110 identifies user input gesture 922. Digital image enhancement system 110 determines a first movement in the horizontal direction and applies a corresponding hue change based on the features detected at the new position 920 and the first movement. Specifically, digital image enhancement system 110 identifies the pixels with hues depicted within the threshold hue range of magenta and applies the change in hue to those pixels. Additionally, digital image enhancement system 110 determines a second movement in the vertical direction and applies a corresponding change in saturation based on the features detected at the new position 920 and the second movement. Specifically, digital image enhancement system 110 identifies the pixels within the threshold hue range of magenta and applies the change in saturation to those pixels. As illustrated, digital image enhancement system 110 generates enhanced digital image 924.

[0125] Although Figures 9A - 9B The figure illustrates the modifications applied to the digital image. As discussed above, digital image enhancement system 110 can iteratively modify the digital image by identifying features at the sensor location and detecting two-dimensional user input gestures. For example, digital image enhancement system 110 can use sensor 910 to detect additional selections at additional locations, identify additional features at the additional locations, determine additional user input gestures, and modify enhanced digital image 916 based on the detected features and the additional user input gesture.

[0126] As mentioned above, in some embodiments, digital image enhancement system 110 can detect an object depicted in the digital image at the sensor location and modify the object based on the user input gesture on the digital image. For example, Figure 10 The figure illustrates a computing device 1000 having a touch screen 1002. Touch screen 1002 displays a digital image enhancement user interface 1004 including a digital image 1006 (i.e., a digital image depicting a statue 1012).

[0127] Digital image enhancement system 110 identifies a user selection (e.g., a long press event) at a first position 1008 corresponding to sensor 1010. In response, digital image enhancement system 110 can determine the features at the first position 1008. As illustrated, digital image enhancement system 110 can utilize the Figure 1 structural input pattern. Thus, digital image enhancement system 110 can detect the object depicted at the first position 1008. Specifically, digital image enhancement system 110 can apply an object identification model and identify statue 1012.

[0128] As discussed above, digital image enhancement system 110 can also map parameters to specific movement directions. For example, regarding Figure 10, the digital image enhancement system 110 can associate saturation with the horizontal direction and hue with the vertical direction.

[0129] As Figure 10 shown, the digital image enhancement system 110 also detects the user input gesture 1014. In response, the digital image enhancement system 110 can modify the parameters of the digital image based on the detected object and the user input gesture. In particular, in the Figure 10 embodiment shown, the digital image enhancement system 110 modifies the saturation of the statue 1012 based on movement in the horizontal direction and modifies the hue of the statue 1012 based on movement in the vertical direction. As shown, the digital image enhancement system 110 generates and displays the enhanced digital image 1016.

[0130] Although Figure 10 the figure shows a digital image depicting a particular type or class of object, the digital image enhancement system 110 can operate in conjunction with various digital images depicting various objects. For example, in some embodiments, the digital image enhancement system 110 detects the sky or clouds depicted at the sensor location in the digital image. The digital image enhancement system 110 can modify the sky or clouds based on the user input gesture.

[0131] In addition, in some embodiments, the digital image depicts multiple instances of an object in the digital image. In some embodiments, the digital image enhancement system 110 can detect a single instance of the object at the sensor location, identify multiple instances of the object in the digital image, and modify the multiple instances of the object based on the user input gesture. By way of illustration, the digital image enhancement system 110 can detect a first face at the sensor location. The digital image enhancement system 110 can analyze the digital image and detect a second face in the digital image. In response to the user input gesture, the digital image enhancement system 110 modifies the first face and the second face (e.g., modifies the hue, brightness, or saturation of the first face and the second face).

[0132] The digital image enhancement system 110 can also set limits on parameter values based on features detected in the digital image. For example, in response to detecting a face in the digital image, the digital image enhancement system 110 can set limits on hue values within a range corresponding to human skin color. Similarly, after detecting the sky in the digital image, the digital image enhancement system 110 can select a range of hue values corresponding to traditional sky colors.

[0133] In addition, in addition to Figures 9A - 10In addition to the features identified, the digital image enhancement system 110 can also identify and modify digital images based on other features. For example, as mentioned above, the digital image enhancement system 110 can detect the time or location within a digital image and select parameters to be modified based on that time or location. For example, the digital image enhancement system 110 can determine that the digital image depicts spring. In response, the digital image enhancement system 110 can select color parameters (e.g., to emphasize the colors of spring flowers). Similarly, the digital image enhancement system 110 can determine that London is depicted in the digital image and select brightness parameters (e.g., to brighten dark areas).

[0134] The digital image enhancement system 110 can also provide additional user interface functionality that aids in generating the enhanced digital image. For example, in some embodiments, the digital image enhancement system 110 alternates between displaying the modified digital image and the previous (e.g., original) digital image (e.g., to assist the user in evaluating the modification). Figure 11 The figure illustrates alternating between displaying the modified digital image and the previous digital image according to one or more embodiments. As Figure 11 shown, the digital image enhancement system 110 displays the enhanced digital image 1016. In response to a user input (e.g., a long press event), the digital image enhancement system 110 can display the digital image 1006 (before modification). Specifically, the digital image enhancement system 110 displays the digital image 1006 for the duration of the user input (e.g., until the long press event is completed). After the user input is completed, the digital image enhancement system 110 displays the enhanced digital image 1016.

[0135] The digital image enhancement system 110 can provide a variety of other user interface functions to assist in modifying the digital image. For example, in response to a user input, the digital image enhancement system 110 can provide details of the modification to the digital image. By way of illustration, the digital image enhancement system 110 can provide text elements indicating the modification to various parameters (e.g., modification to brightness or saturation).

[0136] For example, the digital image enhancement system 110 may provide visual elements within a user interface that provide visual feedback regarding parameter values. For example, in some embodiments, the digital image enhancement system 110 may display digital parameter values as text near a sensor of a touch screen or near a finger position or at a separate fixed location (e.g., at the top or bottom of a view screen). A user may swipe a finger across the text (or provide some other user input) to increase or decrease the value and may alternatively directly enter a text value for the parameter. Moreover, the digital image enhancement system 110 may allow text feedback regarding specific user modes and parameter types for control along two axes. Such visual feedback may include graphical depictions, such as a change in an icon for a sensor visual element. It may also include a visual display of parameter values, such as the presentation of a bar whose length indicates parameter strength. In this manner, the digital image enhancement system 110 may notify a user regarding what changes are being made (or have been made) in generating an enhanced digital image.

[0137] Turning now to Figure 12 , additional details regarding components and capabilities of the digital image enhancement system 110 in accordance with one or more embodiments are provided. As shown, the digital image enhancement system 110 is implemented by a computing device 1200 (e.g., (a) server device(s) 102 and / or client device(s) 104a). Additionally, as illustrated, the digital image enhancement system 110 includes an input mode manager 1202, a sensor engine 1204, a modification manager 1206 (which includes a parameter selector 1208 and a multi-dimensional input engine 1210), and a storage manager 1214 (which stores digital images 1214a, digital image features 1214b, enhanced digital images 1214c, input modes 1214d, and parameters 1214e).

[0138] As just mentioned, the digital image enhancement system 110 includes an input mode manager 1202. The input mode manager 1202 may determine, generate, apply, implement, modify, and / or utilize input modes. For example, as discussed above, the digital image enhancement system 110 may determine input modes that define feature types and / or parameters for utilization in generating an enhanced digital image.

[0139] In addition, as Figure 12As shown, the digital image enhancement system 110 includes a sensor engine 1204. The sensor engine 1204 can generate, display, and / or utilize sensors (e.g., transparent sensors). The sensor engine 1204 can also identify, determine, detect, and / or extract features of a digital image (e.g., features corresponding to sensor positions). For example, the sensor engine 1204 can provide a circular transparent sensor for display based on the selection of a sensor position. As described above, the sensor engine 1204 can also apply a color analysis model and / or an object identification model to determine features corresponding to sensor positions.

[0140] As Figure 12 shown, the digital image enhancement system 110 further includes a modification manager 1206. The modification manager 1206 can identify, determine, and / or select modifications to be applied to a digital image. For example, the digital image enhancement system 110 can identify parameters and parameter values to utilize when modifying a digital image.

[0141] As shown, the modification manager 1206 includes a parameter selector 1208. The parameter selector 1208 can identify, determine, generate, and / or select parameters to be modified in a digital image. For example, the parameter selector 1208 can map a parameter to a user input gesture. For example, as described above, the parameter selector 1208 can select a first parameter and map the first parameter to a first direction. Additionally, the parameter selector 1208 can select a second parameter and map the second parameter to a second direction.

[0142] Figure 12 The figure shows that the modification manager 1206 further includes a multi-dimensional input engine 1210. The multi-dimensional input engine 1210 can identify, determine, detect, and / or analyze user input gestures. For example, the multi-dimensional input engine 1210 can identify user input gestures to determine movements corresponding to different directions. In particular, the multi-dimensional input engine 1210 can identify a first movement in a first direction and a second movement in a second direction. Additionally, the multi-dimensional input engine 1210 can determine parameter values based on user input gestures. For example, as described above, the multi-dimensional input engine 1210 can determine a parameter value for a first parameter based on the movement in the first direction and determine a parameter value for a second parameter based on the movement in the second direction.

[0143] As illustrated, the digital image enhancement system 110 further includes a digital image editing engine 1212. The digital image editing engine 1212 can create, generate, edit, modify, render, and / or display an enhanced digital image. For example, the digital image enhancement system 110 can identify (from the modification manager 1206) modifications and make modifications to the digital image. Additionally, the digital image enhancement system 110 can provide the modified digital image for display.

[0144] As Figure 12 shown, the digital image enhancement system 110 also includes a storage manager 1214. The storage manager 1214 maintains data for the digital image enhancement system 110. The storage manager 1214 can maintain any type, size, or kind of data as needed to perform the functions of the digital image enhancement system 110, including digital images 1214a, digital image features 1214b (e.g., colors or objects depicted in the digital image at different locations), enhanced digital images 1214c, input modes 1214d (e.g., color input mode or lighting input mode), and / or parameters 1214e (e.g., available parameters to be modified and / or historical parameter usage records).

[0145] In one or more embodiments, each component of the digital image enhancement system 110 communicates with each other using any suitable communication technology. Additionally, the components of the digital image enhancement system 110 can communicate with one or more other devices including one or more of the client devices described above. It will be appreciated that although the components of the digital image enhancement system 110 are shown as being separate in Figure 12 , any sub-components can be combined into fewer components - such as being combined into a single component, or divided into more components that can serve a particular implementation. Additionally, although the components of Figure 12 are described in connection with the digital image enhancement system 110, at least some of the components for performing operations in connection with the digital image enhancement system 110 described herein can be implemented on other devices within the environment.

[0146] The components of the digital image enhancement system 110 can include software, hardware, or both. For example, the components of the digital image enhancement system 110 can include one or more instructions stored on a computer-readable storage medium and executable by a processor of one or more computing devices (e.g., computing device 1200). When executed by one or more processors, the computer-executable instructions of the digital image enhancement system 110 can cause the computing device 1200 to perform the methods described herein. Alternatively, the components of the digital image enhancement system 110 can include hardware, such as a dedicated processing device that performs a particular function or group of functions. Additionally or alternatively, the components of the digital image enhancement system 110 can include a combination of computer-executable instructions and hardware.

[0147] In addition, the components of the digital image enhancement system 110 that perform the functions described herein can be implemented, for example, as part of a stand-alone application, as a module of an application, as a plug-in for an application including a content management application, as one or more library functions that can be called by other applications, and / or as a cloud computing model. Thus, the components of the digital image enhancement system 110 can be implemented as part of a stand-alone application on a personal computing device or a mobile device. Alternatively or additionally, the components of the digital image enhancement system 110 can be implemented in any application that allows the creation of marketing content and its delivery to users, including but not limited to applications in ADOBE CREATIVE CLOUD, such as ADOBE LIGHTROOM, ADOBE ILLUSTRATOR, ADOBE PHOTOSHOP, and ADOBE CAMERA RAW. "ADOBE", "CREATIVE CLOUD", "LIGHTROOM", "ILLUSTRATOR", "PHOTOSHOP", and "ADOBE CAMERA RAW" are trademarks and / or registered trademarks of Adobe Inc. in the United States and / or other countries.

[0148] Figures 1 - 12 , corresponding text and examples provide many different systems, methods, and non-transitory computer-readable media for generating a target distribution schedule for distributing electronic communications to individual user / client devices. In addition to the foregoing, embodiments can also be described according to a flowchart including actions for achieving a specific result. For example, Figures 13 - 14 The figure shows a flowchart of an example action sequence according to one or more embodiments.

[0149] Although Figures 13 - 14 the figure shows actions according to some embodiments, alternative embodiments can omit, add, reorder, and / or modify Figures 13 - 14 any of the actions shown in Figures 13 - 14 The actions of Figures 13 - 14 can be performed as part of a method. Alternatively, the non-transitory computer-readable medium can include instructions that, when executed by one or more processors, cause a computing device to perform Figures 13 - 14 the actions of

[0150] For example, Figure 13 The figure shows a series of example actions 1300 for generating an enhanced digital image according to one or more embodiments. As Figure 13As shown, this series of actions includes action 1310 that identifies a user selection of a first position on a digital image. For example, action 1310 may include identifying a user selection of a first position of a digital image within a digital image enhancement user interface. In some embodiments, action 1310 includes: detecting one or more features of the digital image at the first position based on a user selection of the first position of the digital image within the digital image enhancement user interface. Additionally, action 1310 may further include: identifying one or more features of the digital image at the first position within the digital image enhancement user interface based on the user selection of the first position. In one or more embodiments, action 1310 includes providing a sensor for display via the digital image enhancement user interface and detecting user interaction with the sensor at the first position. Thus, in some embodiments, the first position is a sensor position.

[0151] As Figure 13 shown, the series of actions 1300 further includes action 1320 that detects a user input gesture on the digital image in a first direction and a second direction. For example, action 1320 may include detecting a user input gesture on the digital image that includes a first movement in a first direction and a second movement in a second direction. In some embodiments, action 1320 includes receiving, within the digital image enhancement user interface, a user input gesture that includes a two-way movement on the digital image. In one or more embodiments, the digital image enhancement system 110 detects the user input gesture in response to user interaction with the sensor. Additionally, in some embodiments, the first movement is in a horizontal direction and the second movement is in a vertical direction.

[0152] As Figure 13 shown, the series of actions 1300 further includes action 1330 that determines a first modification of a first parameter based on the first direction. For example, action 1330 may include determining a first modification of a first parameter of the digital image to be performed based on the first movement in the first direction. In some embodiments, action 1330 includes determining a first modification of a first parameter of the digital image based on the first movement in the first direction and one or more features of the digital image at the first position.

[0153] As Figure 13As shown, a series of operations 1300 further includes an operation 1340 of determining a second modification of a second parameter based on a second direction. For example, operation 1340 may include determining a second modification of a second parameter of a digital image to be executed based on a second movement in the second direction. In some embodiments, operation 1340 includes determining a second modification of a second parameter of a digital image based on a second movement in the second direction and one or more features of the digital image at a first location. In some embodiments, the first parameter and the second parameter include at least two of the following: hue, saturation, brightness, contrast, exposure, shadow, highlight, black point, white point, vividness, sharpness, color temperature, or chromaticity.

[0154] In addition, in some embodiments, the first parameter and the second parameter reflect features at the first location. For example, the first parameter and the second parameter may include parameters corresponding to a specific feature (e.g., a detected feature range or object). By way of illustration, the first parameter may include a hue parameter for modifying pixels of a digital image that correspond to (e.g., depict) at least one of the following: a detected hue, a detected saturation, a detected brightness, or a detected object. Similarly, the first parameter may include a saturation parameter or a brightness parameter for modifying pixels of a digital image that correspond to (e.g., depict) at least one of the following: a detected hue, a detected saturation, a detected brightness, or a detected object.

[0155] As Figure 13 As shown, a series of operations 1300 further includes an operation 1350 of generating an enhanced digital image based on the first modification and the second modification. For example, operation 1350 may include generating an enhanced digital image by making a first modification to the first parameter and a second modification to the second parameter. In some embodiments, operation 1350 includes providing the enhanced digital image for display.

[0156] In some embodiments, a series of operations 1300 includes detecting one or more features of a digital image at a first location by detecting the hue of the digital image at the first location; determining a first modification of a first parameter of the digital image at the first location based on a first movement in a first direction and the hue of the digital image at the first location; determining a second modification of a second parameter of the digital image at the first location based on a second movement in a second direction and the hue of the digital image at the first location.

[0157] Additionally, in some embodiments, a series of operations 1300 includes detecting one or more features of a digital image at a first location by detecting an object depicted in the digital image at the first location; determining a first modification of a first parameter of the digital image at the first location based on a first movement in a first direction and the object depicted in the digital image at the first location; and determining a second modification of a second parameter of the digital image at the first location based on a second movement in a second direction and the object depicted in the digital image at the first location.

[0158] Further, in one or more embodiments, a series of operations 1300 includes detecting an additional user input gesture associated with enhancing the digital image; and in response to the additional user input gesture, transitioning from displaying the enhanced digital image to displaying the digital image within a digital image enhancement user interface for the duration of the additional user input gesture. For example, operations 1300 may include displaying the enhanced digital image; in response to detecting the additional user input gesture, displaying the digital image; and in response to detecting the completion of the additional user input gesture, displaying the enhanced digital image.

[0159] Additionally, in some embodiments, a series of operations 1300 includes determining a first parameter of the digital image and a second parameter of the digital image based on a first input mode; and in response to detecting a mode selection user input, modifying the first input mode to a second input mode corresponding to a third parameter and a fourth parameter.

[0160] Further, in one or more embodiments, a series of operations 1300 includes a second user selection identifying a second location of the enhanced digital image within the digital image enhancement user interface; detecting a second user input gesture that includes a third movement in a third direction and a fourth movement in a fourth direction; determining a third modification of a third parameter of the enhanced digital image based on the third movement in the third direction and the second input mode; determining a fourth modification of a fourth parameter of the enhanced digital image based on the fourth movement in the fourth direction and the second input mode; and generating an updated enhanced digital image by the third modification of the third parameter and the fourth modification of the fourth parameter.

[0161] For example, in some embodiments, the first input mode corresponds to a first parameter and a second parameter. Additionally, in some embodiments, the second input mode corresponds to a third parameter and a fourth parameter. In one or more embodiments, the first input mode also corresponds to a feature type. Additionally, in one or more embodiments, the second input mode corresponds to a second feature type.

[0162] In some embodiments, a user input gesture that includes bidirectional movement on a digital image includes a first movement in a first direction corresponding to a first modification and a second movement in a second direction corresponding to a second modification; and the enhanced digital image reflects the first modification and the second modification.

[0163] Additionally, in some embodiments, the digital image enhancement user interface does not include visual elements for modifying the parameter value of a first parameter or the parameter value of a second parameter. Further, in one or more embodiments, the digital image enhancement user interface does not include a visual slider element.

[0164] Additionally, Figure 14 FIG. illustrates a series of example operations 1400 for generating an enhanced digital image according to one or more embodiments. As Figure 14 shown, the series of operations 1400 also includes an operation 1410 of identifying one or more features of the digital image at a first location. For example, the operation 1410 may include identifying one or more features of the digital image at the first location based on a user selection at the first location within the digital image enhancement user interface. In some embodiments, the operation 1410 includes: providing a transparent sensor for display at the first location based on a user selection at the first location within the digital image enhancement user interface; and identifying one or more features by analyzing the region of the digital image surrounded by the transparent sensor. The operation 1410 may also include: identifying one or more of the brightness at the first location, the hue at the first location, or an object at the first location.

[0165] As Figure 14 shown, the series of operations 1400 also includes: an operation 1420 of detecting a user input gesture that includes movement to a second location of the digital image. For example, the operation 1420 may include detecting a user input gesture that includes movement to a second location of the digital image within the digital image enhancement user interface. In some embodiments, the operation 1420 includes detecting movement from an initial location of the digital image within the digital image enhancement user interface to a second location of the digital image within the digital image enhancement user interface.

[0166] As Figure 14As shown, a series of operations 1400 further includes: an operation 1430 of determining a modification of a parameter based on a movement and one or more features. For example, operation 1430 may include determining a modification of a parameter of a digital image based on a movement to a second position and one or more features of the digital image at a first position. In some embodiments, operation 1430 includes selecting a parameter based on one or more features of the digital image at the first position; and identifying a parameter value of the parameter based on a second position within a user interface. By way of illustration, operation 1430 may include determining a parameter value of a parameter based on at least one of the following: a relative displacement between the second position and an initial position of a user input gesture; or a mapping between an absolute position of the second position within a digital image enhancement user interface and the parameter value.

[0167] As Figure 14 shown, operation 1440 includes generating an enhanced digital image based on the modification. For example, operation 1440 may include generating an enhanced digital image by making the modification of the parameter.

[0168] In some embodiments, a series of operations 1400 includes: determining a vertical movement and a horizontal movement from a user input gesture that includes a movement to a second position; determining a modification of a parameter of the digital image based on the vertical movement and one or more features of the digital image at the first position; determining an additional modification of an additional parameter of the digital image based on the horizontal movement and one or more features of the digital image at the first position; and generating an enhanced digital image by making the modification of the parameter and the additional modification of the additional parameter.

[0169] In one or more embodiments, a series of operations 1300 and / or a series of operations 1400 includes steps for generating an enhanced digital image by utilizing a two-way movement and one or more features. For example, the algorithms and operations Figures 2 to 4 described may include corresponding structures for performing steps for generating an enhanced digital image by utilizing a two-way movement and one or more features.

[0170] Embodiments of the present disclosure may include or utilize a special purpose or general purpose computer that includes computer hardware, such as, for example, one or more processors and system memory, as discussed in more detail below. Embodiments within the scope of the present disclosure also include physical and other computer-readable media for carrying or storing computer-executable instructions and / or data structures. In particular, one or more of the processes described herein may be at least partially implemented as instructions embodied in a non-transitory computer-readable medium and executable by one or more computing devices (e.g., any of the media content access devices described herein). Generally, a processor (e.g., a microprocessor) receives instructions from a non-transitory computer-readable medium (e.g., memory, etc.) and executes those instructions, thereby performing one or more processes including one or more of the processes described herein.

[0171] A computer-readable medium may be any available medium that can be accessed by a general purpose or special purpose computer system. A computer-readable medium storing computer-executable instructions is a non-transitory computer-readable storage medium (device). A computer-readable medium carrying computer-executable instructions is a transmission medium. Thus, by way of example and not limitation, embodiments of the present disclosure may include at least two distinctly different kinds of computer-readable media: non-transitory computer-readable storage media (devices) and transmission media.

[0172] Non-transitory computer-readable storage media (devices) include RAM, ROM, EEPROM, CD-ROM, solid state drives (“SSD”) (e.g., RAM-based), flash memory, phase change memory (“PCM”), other types of memory, other optical disk storage devices, disk storage devices, or other magnetic storage devices, or any other medium that can be used to store the desired program code components in the form of computer-executable instructions or data structures and that can be accessed by a general purpose or special purpose computer.

[0173] “Network” is defined as one or more data links that enable the transport of electronic data between computer systems and / or modules and / or other electronic devices. When information is transmitted or provided to a computer via a network or other communication connection (either hardwired, wireless, or a combination of hardwired or wireless), the computer properly views the connection as a transmission medium. Transmission media can include a network and / or data link that can be used to carry the desired program code components in the form of computer-executable instructions or data structures and that can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media.

[0174] In addition, when reaching various computer system components, program code components in the form of computer-executable instructions or data structures can be automatically transferred from a transmission medium to a non-transitory computer-readable storage medium (device) (and vice versa). For example, computer-executable instructions or data structures received via a network or data link can be buffered in RAM within a network interface module (such as a "NIC") and then ultimately transferred to a less volatile computer storage medium (device) and / or computer system RAM at the computer system. Thus, it should be understood that non-transitory computer-readable storage medium (devices) can be included in computer system components that also (or even primarily) utilize a transmission medium.

[0175] Computer-executable instructions include, for example, instructions and data that, when executed on a processor, cause a general-purpose computer, a special-purpose computer, or a special-purpose processing device to perform a particular function or group of functions. In some embodiments, computer-executable instructions are executed on a general-purpose computer to transform the general-purpose computer into a special-purpose computer implementing the elements of the present disclosure. Computer-executable instructions can be, for example, binary files, intermediate format instructions (such as assembly language), or even source code. Although the subject matter has been described in language specific to structural features and / or methodological acts, it should be understood that the subject matter defined in the appended claims need not be limited to the features or acts described above. Rather, the described features and acts are disclosed as example forms for implementing the claims.

[0176] Those skilled in the art will understand that the present disclosure can be practiced in a network computing environment having many types of computer system configurations, including personal computers, desktop computers, laptop computers, messaging processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, tablet computers, pagers, routers, switches, etc. The present disclosure can also be practiced in a distributed system environment where local and remote computer systems linked by a network (either by a hardwired data link, a wireless data link, or a combination of hardwired and wireless data links) both perform tasks. In a distributed system environment, program modules can be located in local and remote memory storage devices.

[0177] Embodiments of the present disclosure can also be implemented in a cloud computing environment. In this specification, "cloud computing" is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources. For example, cloud computing can be adopted in the market to provide ubiquitous and convenient on-demand access to a shared pool of configurable computing resources. A shared pool of configurable computing resources can be rapidly provisioned via virtualization and released with less management effort or service provider interaction, and then scaled accordingly.

[0178] Cloud computing models can consist of various characteristics such as, for example, on-demand self-service, broad network access, resource pooling, rapid elasticity, measured service, and so on. Cloud computing models can also expose various service models such as, for example, Software as a Service (“SaaS”), Platform as a Service (“PaaS”), and Infrastructure as a Service (“IaaS”). Different deployment models such as private cloud, community cloud, public cloud, hybrid cloud, and so on can also be used to deploy cloud computing models. In this specification and the claims, a “cloud computing environment” is an environment in which cloud computing is adopted.

[0179] Figure 15 An example computing device 1500 (e.g., client devices 104a - 104n; and / or server device(s) 102; computing devices 302, 402, 500, 700, 900, or 1000; and / or computing device 1200) that can be configured to perform one or more of the above processes is illustrated in block diagram form. It will be appreciated that the digital image enhancement system 110 can include an implementation of the computing device 1500. As Figure 15 shown, the computing device can include a processor 1502, a memory 1504, a storage device 1506, an I / O interface 1508, and a communication interface 1510. In addition, the computing device 1500 can include input devices such as a touch screen, a mouse, and so on. In certain embodiments, the computing device 1500 can include fewer or more components than Figure 15 shown. The components of the computing device 1500 shown in Figure 15 will now be described in more detail.

[0180] In a particular embodiment, the processor(s) 1502 includes hardware for executing instructions such as those that make up a computer program. By way of example and not limitation, to execute instructions, the processor(s) 1502 can retrieve (or fetch) instructions from internal registers, internal caches, memory 1504, or storage device 1506, and decode and execute them.

[0181] The computing device 1500 includes a memory 1504 that is coupled to the processor(s) 1502. The memory 1504 can be used to store data, metadata, and programs executed by the processor(s). The memory 1504 can include one or more of volatile and non-volatile memories such as random access memory (“RAM”), read-only memory (“ROM”), solid state disk (“SSD”), flash memory, phase change memory (“PCM”), or other types of data storage devices. The memory 1504 can be internal or distributed memory.

[0182] The computing device 1500 includes a storage device 1506, which includes a storage device for storing data or instructions. By way of example and without limitation, the storage device 1506 may include the above-mentioned non-transitory storage medium. The storage device 1506 may include a hard disk drive (HDD), flash memory, a universal serial bus (USB) drive, or a combination of these or other storage devices.

[0183] The computing device 1500 also includes one or more input or output (“I / O”) device / interfaces 1508, which are provided to allow a user to provide input to the computing device 1500 (such as a user stroke), receive output from the computing device 1500, and otherwise transfer data to and from the computing device 1500. These I / O device / interfaces 1508 may include a mouse, keypad or keyboard, touch screen, camera, optical scanner, network interface, modem, other known I / O devices, or a combination of these I / O device / interfaces 1508. The touch screen can be activated with a writing device or a finger.

[0184] The I / O device / interface 1508 may include one or more devices for presenting output to the user, including but not limited to a graphics engine, a display (e.g., a display screen), one or more output drivers (e.g., a display driver), one or more audio speakers, and one or more audio drivers. In some embodiments, the device / interface 1508 is configured to provide graphic data to the display for presentation to the user. The graphic data may represent one or more graphical user interfaces and / or any other graphic content that may serve a particular implementation.

[0185] The computing device 1500 may also include a communication interface 1510. The communication interface 1510 may include hardware, software, or both. The communication interface 1510 may provide one or more interfaces for communication between the computing device and one or more other computing devices 1500 or one or more networks (such as, for example, packet-based communication). By way of example and without limitation, the communication interface 1510 may include a network interface controller (NIC) or network adapter for communicating with an Ethernet or other wired-based network, or a wireless NIC (WNIC) or wireless adapter for communicating with a wireless network (such as WI-FI). The computing device 1500 may also include a bus 1512. The bus 1512 may include hardware, software, or both that couple the components of the computing device 1500 to each other.

[0186] In the foregoing specification, the present invention has been described with reference to specific example embodiments of the present invention. Various embodiments and aspects of the present invention have been described with reference to the details discussed herein and the accompanying drawings which illustrate the various embodiments. The above description and the drawings are illustrative of the present invention and should not be construed as limiting the present invention. Numerous specific details have been described to provide a thorough understanding of the various embodiments of the present invention.

[0187] The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. For example, the methods described herein may be performed with fewer or more steps / actions, or the steps / actions may be performed in a different order. Additionally, the steps / actions described herein may be repeated or performed in parallel with each other or with different instances of the same or similar steps / actions. Accordingly, the scope of the present invention is indicated by the appended claims rather than by the foregoing description. All changes that come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims

1. A non-transitory computer-readable medium storing instructions thereon, which when executed by at least one processor cause a computing device to: Receive a user selection of a structural pattern corresponding to an object identification model from among multiple patterns via a digital image enhanced user interface; Identify a user selection of a first location of a digital image within the digital image enhanced user interface; Provide a visual sensor for display via the digital image enhanced user interface, the visual sensor indicating an area to be processed based on the user selection of the first location; Based on the user selection of the structural pattern, identify an object class corresponding to an object depicted in the digital image within the area of the visual sensor by processing the area of the visual sensor of the digital image using the object identification model; Detect a user input gesture on the digital image, the user input gesture including a first movement in a first direction and a second movement in a second direction; Based on the first movement in the first direction, determine a first modification of a first parameter of the digital image to be executed, wherein the first parameter is selected based on the object class corresponding to the object depicted in the digital image at the first location; Based on the second movement in the second direction, determine a second modification of a second parameter of the digital image to be executed, wherein the second parameter is selected based on the object class corresponding to the object depicted in the digital image at the first location; And Generate an enhanced digital image by making the first modification to the first parameter and the second modification to the second parameter.

2. The non-transitory computer-readable medium according to claim 1, wherein the digital image enhanced user interface does not include visual elements for modifying the parameter value of the first parameter or the parameter value of the second parameter.

3. The non-transitory computer-readable medium according to claim 1, further storing instructions thereon, which when executed by the at least one processor cause the computing device to identify the object within the area of the visual sensor by: Detecting an object within the digital image by using the object identification model; and Based on detecting the object within the digital image, identifying a portion of the object within the area of the visual sensor.

4. The non-transitory computer-readable medium according to claim 1, further storing instructions thereon, which when executed by the at least one processor cause the computing device to: Identify one or more additional features of the digital image; and Based on the first movement in the first direction, the object class of the object depicted in the digital image within the area of the visual sensor, and the one or more additional features, determine the first modification of the first parameter of the digital image at the first location.

5. The non-transitory computer-readable medium according to claim 4, further storing instructions that, when executed by the at least one processor, cause the computing device to: detect one or more additional features of the digital image at the first location by detecting a geographical location depicted in the digital image; determine a first modification of the first parameter of the digital image based on the first movement in the first direction, the object class of the object depicted in the digital image within the region of the vision sensor, and the geographical location depicted in the digital image.

6. The non-transitory computer-readable medium according to claim 1, wherein the first parameter and the second parameter include at least two of the following: hue, saturation, brightness, contrast, exposure, shadow, highlight, black point, white point, vividness, sharpness, color temperature, or chroma.

7. The non-transitory computer-readable medium according to claim 4, further storing instructions that, when executed by the at least one processor, cause the computing device to: determine a second modification of the second parameter of the digital image based on the second movement in the second direction, the one or more additional features of the digital image, and the object depicted in the digital image within the region of the vision sensor.

8. The non-transitory computer-readable medium according to claim 1, further storing instructions that, when executed by the at least one processor, cause the computing device to: detect an additional user input gesture associated with the enhanced digital image; and in response to the additional user input gesture, during the duration of the additional user input gesture, transition from displaying the enhanced digital image to displaying the digital image within the digital image enhancement user interface.

9. The non-transitory computer-readable medium according to claim 1, further storing instructions that, when executed by the at least one processor, cause the computing device to: determine the first parameter of the digital image and the second parameter of the digital image based on a first input mode; and in response to detecting a mode selection user input, modify the first input mode to a second input mode corresponding to third and fourth parameters.

10. The non-transitory computer-readable medium according to claim 9, further storing instructions that, when executed by the at least one processor, cause the computing device to: identify a second user selection of a second location of the enhanced digital image within the digital image enhancement user interface; detect a second user input gesture, the second user input gesture including a third movement in a third direction and a fourth movement in a fourth direction; determine a third modification of the third parameter of the enhanced digital image based on the third movement in the third direction and the second input mode; determine a fourth modification of the fourth parameter of the enhanced digital image based on the fourth movement in the fourth direction and the second input mode; and and Generate an updated enhanced digital image by performing the third modification on the third parameter and the fourth modification on the fourth parameter.

11. A system for generating an enhanced digital image, comprising: At least one processor; And At least one non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to: Receive a user selection of a structural pattern corresponding to an object identification model from among a plurality of patterns via a digital image enhancement user interface; Identify a user selection of a first location on the digital image within the digital image enhancement user interface; Provide a visual sensor for display via the digital image enhancement user interface, the visual sensor indicating an area to be processed based on the user selection of the first location; Based on the user selection of the structural pattern, identify, from a plurality of object classes, an object class corresponding to an object depicted in the area of the visual sensor of the digital image by processing the area of the visual sensor of the digital image using the object identification model; Detect a user input gesture, the user input gesture including a movement to a second location on the digital image within the digital image enhancement user interface; Determine a modification to a parameter of the digital image based on the movement to the second location and the object class corresponding to the object depicted in the digital image at the first location; And Generate the enhanced digital image by performing the modification on the parameter.

12. The system according to claim 11, further comprising instructions that, when executed by the at least one processor, cause the system to identify the object within the area of the visual sensor by: Identifying an object within the digital image by using the object identification model; and Identifying a portion of the object within the area of the visual sensor.

13. The system according to claim 11, further storing instructions that, when executed by the at least one processor, cause the system to: Identify one or more additional features of the digital image; and Determine the modification to the parameter of the digital image at the first location based on the movement, the object class of the object depicted in the area of the visual sensor of the digital image, and the one or more additional features.

14. The system according to claim 11, further storing instructions that, when executed by the at least one processor, cause the system to determine the modification to the parameter of the digital image by identifying a parameter value of the parameter based on the second location within the digital image enhancement user interface.

15. The system according to claim 14, further storing instructions that, when executed by the at least one processor, cause the system to determine the parameter value of the parameter based on the second location based on at least one of: A relative displacement between the second location and an initial location of the user input gesture; or The mapping between the absolute position of the second position within the digital image enhancement user interface and the parameter value.

16. The system according to claim 15, further storing instructions that, when executed by the at least one processor, cause the system to: Determine a vertical movement and a horizontal movement from the user input gesture including the movement to the second position; Based on the vertical movement and the object class of the object depicted in the digital image at the first position, determine the modification of the parameter of the digital image; Based on the horizontal movement and the object class of the object depicted in the digital image at the first position, determine an additional modification of an additional parameter of the digital image; And Generate the enhanced digital image by making the modification of the parameter and the additional modification of the additional parameter.

17. A computer-implemented method for effectively generating a modified digital image, comprising: Receiving, via a digital image enhancement user interface, a user selection of a structural pattern corresponding to an object identification model from a plurality of patterns; Identifying, within the digital image enhancement user interface, a user selection of a first position of a digital image; Providing a visual sensor for display via the digital image enhancement user interface, the visual sensor indicating an area to be processed based on the user selection of the first position; Based on the user selection of the structural pattern, identifying, from a plurality of object classes, an object class corresponding to an object depicted in the area of the visual sensor of the digital image by processing the area of the visual sensor of the digital image using the object identification model; Receiving, within the digital image enhancement user interface, a user input gesture including a two-way movement on the digital image; Selecting a first modification and a second modification based on the object class corresponding to the object depicted in the digital image at the first position; And Generating an enhanced digital image by applying the first modification and the second modification according to the two-way movement.

18. The computer-implemented method according to claim 17, wherein the digital image enhancement user interface does not include a visual slider element.

19. The computer-implemented method according to claim 17, further comprising selecting the first modification and the second modification based on one or more additional features of the digital image at the first position, wherein the one or more additional features include the time depicted in the digital image.

20. The computer-implemented method according to claim 17, wherein the user input gesture including the two-way movement on the digital image includes a first movement in a vertical direction corresponding to the first modification and a second movement in a horizontal direction corresponding to the second modification.

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