Electronic apparatus and control method thereof

Abstract

The electronic device includes a processor that identifies the display environment of an image, corrects the characteristics of a provided test image to correspond to the display environment to identify the user’s visibility regarding the characteristics of the image, controls the display of the corrected test image on a display, and corrects the characteristics of the image based on the user’s adjustment input regarding the characteristics of the displayed test image.

Description

Technology Field

[0001] The present invention relates to an electronic device for processing an image signal and a control method thereof so that an image based on the image signal is displayed, and more specifically, to an electronic device and a control method thereof configured to correct user perception distortion regarding the image. Background Technology

[0002] Electronic devices, which fundamentally include electronic components such as CPUs, chipsets, and memory for computation to perform calculations and process specific information according to a particular process, can be classified into various types depending on the information to be processed or the intended use. For example, electronic devices include information processing devices such as PCs or servers that process general-purpose information, image processing devices that process image data, audio devices that process audio, and household appliances that perform chores within the home. Image processing devices can be classified into devices equipped with a display panel for displaying images (i.e., display devices) and devices that do not have a display panel. A display device can process an image signal provided from an image source and display it on its own display panel, while an image processing device without a display panel outputs the processed image signal to a display device, thereby enabling the image to be displayed on that device.

[0003] Images displayed in this manner may have factors that degrade the user's ability to perceive them accurately. For example, there is the color wash-out phenomenon, which is a situation where the higher the brightness visually perceived by the user, the lower the saturation of the image perceived by the user becomes. Furthermore, each user has a unique ability to perceive images. For this reason, even if users view images displayed on the same display device under the same surrounding environment, the color tone of the image perceived by each user may differ. In other words, distortion of the image perceived by the user may occur due to various factors involved in the user's perception of the image. Prior art is disclosed in Korean Patent Publication No. 10-2018-0078713 (published July 10, 2018), Korean Patent Publication No. 10-2017-0030699 (published March 20, 2017), and Korean Patent Publication No. 10-2017-0074909 (published June 30, 2017).

[0004] An image processing device or display device may be required to reduce such distortion in image perception and to ensure that the image characteristics (e.g., color) intended by the provider of the image content are conveyed to the user as accurately as possible. means of solving the problem

[0005] An electronic device according to an embodiment of the present invention includes a processor that identifies a display environment of an image, corrects the characteristics of a test image provided to identify a user’s visibility regarding the characteristics of the image to correspond to the identified display environment, controls the corrected test image to be displayed on a display, and corrects the characteristics of the image based on a user’s adjustment input regarding the characteristics of the displayed test image.

[0006] Additionally, the display environment includes at least one of the brightness of the display or the ambient brightness, and the processor can correct the characteristics of the test image in correspondence with the brightness of the display and the ambient brightness.

[0007] In addition, the processor can correct the saturation of each color of the test image.

[0008] Additionally, the processor may identify a first correction value defined to be proportional to at least one of the brightness of the display or the ambient brightness, and reflect the first correction value in the value of the characteristic of the test image.

[0009] Additionally, the system further includes an interface unit for receiving a video signal, and the processor can correct the characteristics of the video by reflecting the first correction value and the second correction value based on the adjustment input together in the color information of the video signal received through the interface unit.

[0010] In addition, the processor may reflect a pre-defined third correction value inversely proportional to the first correction value in the brightness information of the video signal received through the interface unit.

[0011] In addition, the processor can calculate the first correction value by summing the correction value corresponding to the brightness of the display and the correction value corresponding to the ambient brightness.

[0012] In addition, the processor can calculate the first correction value by assigning different weights to each of the correction value corresponding to the brightness of the display and the correction value corresponding to the ambient brightness.

[0013] Additionally, the device further includes an interface unit for receiving a video signal, and the processor can correct the characteristics of the video by reflecting a second correction value based on the adjustment input to the color information of the video signal received through the interface unit.

[0014] Additionally, the test image includes a plurality of divided regions having the same color, and one of the plurality of regions has a different saturation from the remaining regions, and the processor can measure a user's score for the color in response to whether the adjustment input normally selects the region with the different saturation, and derive the second correction value based on the measured score.

[0015] Additionally, the device further includes a storage unit that stores a second correction value corresponding to a user, and the processor acquires the second correction value stored in the storage unit when displaying the image, and can adjust the second correction value based on the difference between the display environment at the time of derivation of the second correction value and the display environment at the current time.

[0016] In addition, a control method for an electronic device according to an embodiment of the present invention comprises: a step of identifying a display environment of an image; a step of correcting the characteristics of a test image provided to identify user visibility regarding the characteristics of the image to correspond to the identified display environment; a step of controlling the corrected test image to be displayed on a display; and a step of correcting the characteristics of the image based on user adjustment input regarding the characteristics of the displayed test image. Brief explanation of the drawing

[0017] Figure 1 is an example diagram of an electronic device. Figure 2 is a block diagram of an electronic device. Figure 3 is a flowchart showing a control method for an electronic device. FIG. 4 is a block diagram showing an embodiment in which an electronic device corrects the characteristics of an image. FIG. 5 is a block diagram showing another embodiment in which an electronic device corrects the characteristics of an image. Figure 6 is an example diagram illustrating the principle of identifying the first correction value. Figure 7 is a graph showing the curve of the correction values ​​by color. Figure 8 is an example diagram illustrating the principle of determining saturation correction values ​​according to display brightness through a perception experiment. Figure 9 is an example diagram illustrating the principle of determining saturation correction values ​​according to ambient brightness through a perception experiment. Figure 10 is an example diagram showing an electronic device performing a user cognitive characteristic test. FIG. 11 is a block diagram illustrating the principle of an electronic device managing and applying image perception characteristic correction values ​​for each user. FIG. 12 is a flowchart illustrating the process of an electronic device adjusting a correction value in response to environmental changes. Specific details for implementing the invention

[0018] Embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. Unless otherwise noted, the embodiments described with reference to each drawing are not mutually exclusive and multiple embodiments may be selectively combined and implemented within a single device. Such combinations of multiple embodiments may be arbitrarily selected and applied by a person skilled in the art to implement the concept of the present invention.

[0019] If, in the embodiments, terms including ordinal numbers such as "first component," "second component," etc. are used, such terms are used to describe various components and to distinguish one component from another; therefore, the meaning of these components is not limited by the terms. The terms used in the embodiments are applied to describe the corresponding embodiments and do not limit the scope of the invention.

[0020] Additionally, where the expression "at least one" appears among the plurality of components in this specification, this expression refers not only to all of the plurality of components but also to each individual component excluding the rest, or any combination thereof.

[0021] Figure 1 is an example diagram of an electronic device.

[0022] As illustrated in FIG. 1, the electronic device (100) according to the present embodiment is implemented as a display device having a display unit (110). However, the concept of the present invention is not necessarily limited to being applied only to a display device, and may also be applied to an image processing device that processes an image signal and outputs it to a separate display device without having a display unit (110). The electronic device (100) can be implemented as various types of devices, for example, a fixed display device including a TV, monitor, digital signage, electronic whiteboard, electronic picture frame, video wall, etc.; a mobile device including a smartphone, tablet device, portable multimedia player, etc.; a wearable device; or an image processing device including a set-top box, relay device, optical media player, etc. Examples of implementation are possible.

[0023] The image displayed on the display unit (110) of the electronic device (100) is perceived by the user (101). At this time, the user's (101) perception of the image largely depends on two factors: the image display environment and the user's (101) perception ability. Here, the image display environment includes elements of the device environment of the electronic device (100) and elements of the surrounding environment of the electronic device (100). For example, the image perceived by the user (101) is influenced by light L1 emitted from the display unit (110) and ambient light L2. In summary, the image perceived by the user (101) is influenced by three factors: the device characteristics of the electronic device (100), the characteristics of the surrounding environment where the electronic device (100) is installed, and the perception characteristics of the user (101) themselves who perceives the image.

[0024] The device characteristics of the electronic device (100) include, for example, the brightness of the display unit (110) that displays an image. When the user (101) perceives the image, the intensity of the saturation perceived by the user (101) varies depending on the brightness of the display unit (110). For example, when an image of the same color is displayed on each of two display units (110) with different brightness levels, the user (101) typically perceives the saturation in the image displayed on the display unit (110) with relatively higher brightness as lower. This situation may occur frequently as the limit of the maximum brightness that the display unit (110) can express becomes increasingly higher.

[0025] The characteristics of the surrounding environment in which the electronic device (100) is installed include, for example, the brightness of the environment of the place where the user (101) views the image of the electronic device (100). For example, when there is a light (102) in the room where the electronic device (100) is located, the user (101) perceives the saturation of the image when the light (102) is on and the saturation of the image when the light (102) is off differently. When the user (101) views the image, the intensity of the perceived saturation changes depending on the brightness of the surrounding environment. Similar to the case of the brightness of the display unit (110) described above, the higher the brightness of the ambient light, the lower the saturation of the image felt by the user (101).

[0026] The cognitive characteristics of the user (101) indicate that the characteristics of the image are perceived differently depending on the subjective sense of the user (101), for example. For example, even if two users (101) are watching an image displayed on a display unit (110) that emits light quantity L1 under an ambient environment of ambient light L2, the color or saturation of the image perceived by each user (101) may be different from each other.

[0027] The electronic device (100) according to an embodiment of the present invention operates to minimize distortion of the image perceived by the user (101) by taking all of these matters into consideration. A detailed explanation regarding this will be provided later.

[0028] Figure 2 is a block diagram of an electronic device.

[0029] As illustrated in FIG. 2, the electronic device (100) includes various hardware components necessary for operation. The components included in the electronic device (100) are not limited to this example only, and additional components may be included as needed during the implementation of the electronic device (100), or some components shown in this example may not be included. For example, if the electronic device (100) does not include a display unit (110), it may be configured to output a video signal to another display device through an interface unit (120).

[0030] The electronic device (100) may include a display unit (110). The display unit (110) includes a display panel capable of displaying an image on a screen. The display panel is provided with a light-receiving structure such as a liquid crystal method or a self-emissive structure such as an OLED method. Depending on the structure of the display panel, the display unit (110) may additionally include additional components. For example, if the display panel is a liquid crystal method, the display unit (110) includes a liquid crystal display panel, a backlight unit that supplies light, and a panel driving board that drives the liquid crystal of the liquid crystal display panel.

[0031] The electronic device (100) may include an interface unit (120). The interface unit (120) includes an interface circuit for the electronic device (100) to communicate with various types of external devices and to transmit and receive data. The interface unit (120) is configured to enable communication with multiple external devices in parallel. For example, the interface unit (120) includes multiple communication means described below, and may communicate with multiple external devices using the same communication means, or may communicate with each of the multiple external devices using different communication means.

[0032] The interface unit (120) may include one or more wired interface units (121) for wired communication connection. The wired interface unit (121) includes a connector or port to which a cable of a predefined transmission standard is connected. For example, the wired interface unit (121) includes a port to which a cable of a cable broadcasting system is connected to a terrestrial or satellite broadcasting antenna to receive a broadcast signal, or to which a cable of a cable broadcasting system is connected. Alternatively, the wired interface unit (121) includes a port to which a cable of various wired transmission standards, such as HDMI, DP, DVI, component, composite, S-Video, or Thunderbolt, is connected to connect to various video processing devices. Alternatively, the wired interface unit (121) includes a USB standard port to connect to a USB device. Alternatively, the wired interface unit (121) includes an optical port to which an optical cable is connected. Alternatively, the wired interface unit (121) includes an audio input port to which an external microphone is connected, and an audio output port to which a headset, earphones, external speakers, etc. are connected. Alternatively, the wired interface section (121) includes an Ethernet port for connecting to a gateway, router, hub, etc., to connect to a wide area network.

[0033] The interface unit (120) may include one or more wireless interface units (122) for wireless communication connection. The wireless interface unit (122) includes a bidirectional communication circuit comprising at least one of components such as a communication module and a communication chip corresponding to various types of wireless communication protocols. For example, the wireless interface unit (122) includes a Wi-Fi communication chip that performs wireless communication with an AP according to the Wi-Fi method, a communication chip that performs wireless communication such as Bluetooth, Zigbee, Z-Wave, WirelessHD, WiGig, NFC, an IR module for IR communication, and a mobile communication chip that performs mobile communication with a mobile device.

[0034] The electronic device (100) may include a user input unit (130). The user input unit (130) includes various types of input interface-related circuits provided to allow the user to operate in order to perform user input. The user input unit (130) can be configured in various forms depending on the type of electronic device (100), for example, a mechanical or electronic button unit of the electronic device (100), a touchpad, a sensor, a camera, a touchscreen installed on the display unit (110), a remote controller separated from the main body of the electronic device (100), etc.

[0035] Meanwhile, depending on the design method, the electronic device (100) may further include a microphone for collecting the user's voice and generating an audio signal. The microphone may be provided in the main body of the electronic device (100) or in a remote controller separated from the main body of the electronic device (100). When the microphone is provided in the remote controller, the remote controller converts the audio signal received through the microphone into a carrier signal for wireless transmission and transmits it to the wireless interface unit (122).

[0036] Meanwhile, the means for inputting the user's voice into the electronic device (100) is not limited to a microphone provided in the electronic device (100), and voice input can also be performed by a separate external device communicating with the electronic device (100). For example, if the electronic device (100) is a TV, the operation of the electronic device (100) can be controlled through the mobile device by installing a TV control application provided in advance on a mobile device such as a smartphone or tablet device. Here, the TV control application is provided to process an audio signal corresponding to the user's voice when the TV supports a voice recognition function. If the mobile device is equipped with a microphone, the mobile device can receive the user's voice through the microphone of the mobile device while the TV control application is operating. The mobile device converts the received audio signal of the user's voice into a carrier signal and transmits it to the wireless interface unit (122).

[0037] Meanwhile, the aforementioned external device is not limited to mobile devices only, but includes various types of electronic devices, such as AI speakers, that are fixedly installed or portable, and are configured to have a TV control application installed and executed.

[0038] The electronic device (100) may include a storage unit (140). The storage unit (140) stores digitized data. The storage unit (140) includes storage with non-volatile properties that can preserve data regardless of whether power is provided, and memory with volatile properties where data to be processed by the processor (160) is loaded and data cannot be preserved if power is not provided. Storage includes flash memory, hard-disc drive (HDD), solid-state drive (SSD), and ROM (Read Only Memory), and memory includes buffer and RAM (Random Access Memory). The storage unit (140) according to the present embodiment may store, for example, the user account of the electronic device (100), the manufacturer, brand, device information of the electronic device (100).

[0039] The storage unit (140) according to the present embodiment may store, for example, data of a predefined test image. The test image is prepared in advance to identify the user's visibility regarding a predetermined characteristic of the image displayed on the display unit (110) and is stored in the storage unit (140). However, the data of the test image does not necessarily have to be stored in the storage unit (140), and it is also possible for the electronic device (100) to receive the data of the test image through the interface unit (120) when necessary.

[0040] The electronic device (100) may include a sensor (150). The sensor (150) detects the amount of light or brightness of the surrounding environment of the electronic device (100) and transmits it to the processor (160). The sensor (150) may include, for example, a photosensor, a camera, etc. However, the method by which the processor (160) obtains information regarding the brightness of the surrounding environment is not limited to the sensor (150). Depending on the design method, the electronic device (100) may not include the sensor (150), and it is also possible to receive information regarding the brightness of the surrounding environment through the interface unit (120).

[0041] The electronic device (100) may include a processor (160). The processor (160) includes one or more hardware processors, such as a CPU, chipset, buffer, and circuit, which are mounted on a printed circuit board, and may be implemented as a system on chip (SOC) depending on the design method. When the electronic device (100) is implemented as a display device, the processor (160) includes modules corresponding to various processes, such as a demultiplexer, decoder, scaler, audio DSP (Digital Signal Processor), and amplifier. Here, some or all of these modules may be implemented as an SOC. For example, modules related to image processing, such as a demultiplexer, decoder, and scaler, may be implemented as an image processing SOC, and the audio DSP may be implemented as a chipset separate from the SOC.

[0042] The processor (160) according to the present embodiment performs an operation to minimize user perception distortion regarding the characteristics of an image displayed on the display unit (110). The operation is described below.

[0043] Figure 3 is a flowchart showing a control method for an electronic device.

[0044] As illustrated in FIG. 3, the following operation is performed by a processor (160, see FIG. 2) of an electronic device (100, see FIG. 2).

[0045] In step 310, the electronic device identifies the image display environment. The image display environment may be, for example, the brightness of the display unit (110, see FIG. 2) of the electronic device and the brightness of the surrounding environment of the electronic device. On the other hand, if the electronic device is configured to output an image signal so that the image is displayed on another display device, the image display environment may include the brightness of the display unit provided in the other display device.

[0046] In step 320, the electronic device corrects the characteristics of a test image, which are provided to identify the user's visibility regarding the characteristics of the image, to correspond to the identified display environment. The characteristics of the image include, for example, the color and saturation of the image.

[0047] In step 330, the electronic device displays the corrected test image. If the electronic device includes a display unit, the electronic device displays the test image on its own display unit. On the other hand, if the electronic device does not include a display unit, it outputs the corrected test image to be displayed on another display device.

[0048] In step 340, the electronic device receives user adjustment input regarding the characteristics of the displayed test image. The electronic device receives user input from the user input unit (130, see FIG. 2). On the other hand, if the test image is displayed on another display device and the other display device is provided with a user input unit, the electronic device may receive a signal regarding user adjustment input from the other display device.

[0049] In step 350, the electronic device corrects the characteristics of the image based on the received user adjustment input. If the electronic device includes a display unit, the electronic device displays the corrected image on its own display unit. On the other hand, if the electronic device does not include a display unit, it outputs an image signal regarding the corrected image to be displayed on another display device.

[0050] Thus, the electronic device minimizes user perception distortion regarding the characteristics of the displayed image, thereby enabling the characteristics of the image intended by the content provider to be conveyed to the user as accurately as possible.

[0051] The above-described operation may be performed by the electronic device alone. However, depending on the design method, the electronic device and a separate device (e.g., a server) that communicates with the electronic device may share and perform multiple stages of the operation within the system. As one example, the electronic device may perform only basic input / output operations, while a server with higher system resource availability than the electronic device may perform analysis and correction operations based on the input / output content received from the electronic device and transmit the results to the electronic device. For example, in this embodiment, the electronic device may be configured to perform user input (step 340) and display of a test image (step 330), and the server may perform key identification operations and correction operations (steps 310, 320, 350) and transmit the results to the electronic device. In this case, the key operations are performed by the server, and the electronic device performs only the operation of transmitting input information to the server or outputting results received from the server.

[0052] Specifically, in step 310, the server identifies the image display environment in the electronic device based on information about the surrounding environment received from the electronic device. Depending on the design method, the electronic device may perform step 310, in which case the electronic device transmits the identified information regarding the image display environment to the server.

[0053] In step 320, the server corrects the characteristics of the test image to correspond to the identified display environment and transmits the corrected result to the electronic device.

[0054] In step 330, the electronic device displays a corrected test image based on the corrected result received from the server. Here, the electronic device may correct the test image itself by receiving an offset value for the correction of the test image from the server while the test image is stored in advance, or it may simply receive the data of the test image corrected by the server and display it as is.

[0055] In step 340, the electronic device receives user adjustment input regarding the characteristics of the test image and transmits it to the server.

[0056] In step 350, the server corrects the characteristics of the image based on the user's adjustment input received from the electronic device and transmits the corrected result to the electronic device. Accordingly, the electronic device corrects the characteristics of the image based on the corrected result received from the server and can display the corrected image.

[0057] Hereinafter, an embodiment in which an electronic device corrects the characteristics of an image will be described in detail.

[0058] FIG. 4 is a block diagram showing an embodiment in which an electronic device corrects the characteristics of an image.

[0059] As illustrated in FIG. 4, the electronic device (100) performs a first correction value identification step (410). This step (410) corresponds to steps 310 and 320 of FIG. 3. The electronic device (100) obtains two parameters at the current time: the brightness of the display and the ambient brightness. The electronic device (100) identifies a first correction value corresponding to the two obtained parameters. There are various methods for identifying the first correction value, such as searching for a first correction value corresponding to the two parameters from a DB or table based on previously executed test data or simulation data, or calculating a first correction value as a result by substituting the two parameters into a predefined formula or function.

[0060] The first correction value is a value relating to one of the various characteristics that implement an image, and its type is not limited. As one of various examples, the present embodiment describes a case where the first correction value is an offset value for saturation at a predetermined color.

[0061] The electronic device (100) performs a user perception characteristic test step (420). This step (420) corresponds to steps 330 and 340 of FIG. 3. The electronic device (100) displays a pre-prepared test image to provide it to the user, and displays it by reflecting the first correction value identified in the first correction value identification step (410) in the test image. Regarding how the test image is displayed, a default value is defined in the electronic device (100). For example, when displaying a test image regarding a specific color, the level at which the saturation of the test image is displayed is determined as a default value. Accordingly, the electronic device (100) adjusts this default value by applying the first correction value, thereby ensuring that the test image is displayed with the saturation adjusted. As a result, the user sees a test image that is adjusted to correspond to the brightness of the display and the ambient brightness.

[0062] In the user perception characteristic test step (420), the electronic device (100) receives user adjustment input regarding the characteristics of the test image being displayed, for example, user adjustment input regarding the saturation of each color of the test image. The method of user input varies depending on the implementation method of the test image, and examples thereof can be provided in various ways depending on the design method. Specific methods regarding this will be described later.

[0063] The electronic device (100) performs a second correction value identification step (430). Reflecting the received result regarding the user's adjustment input performed in the user perception characteristic test step (420), the electronic device (100) identifies the second correction value. While the first correction value is a correction value for the test image displayed in the user perception characteristic test step (420), the second correction value is a correction value for the image to be displayed by the electronic device (100) (or an image to be processed for display on another display device). The second correction value may be a characteristic value of various images depending on the design method, for example, it may be an offset value of the saturation for a specific color of the image.

[0064] The electronic device (100) performs a brightness and color separation step (440). The electronic device (100) separates and obtains color information and brightness information from a predetermined input image signal. The input image signal can be of various formats, such as RGB, YCbCr, CIE Lab, HSV (hue-saturation-value), CIECAM02, etc. For example, when the input image signal is in the YCbCr format, the electronic device (100) separates Y, which is brightness information, and Cb and Cr, which are color information.

[0065] The electronic device (100) performs a color adjustment step (450). The second correction value identification step (430) and the color adjustment step (450) correspond to step 350 of FIG. 3. The electronic device (100) adjusts the color information of the input video signal by reflecting the second correction value, and converts the adjusted color information into an output video signal by combining it with brightness information. The output video signal is the result of the input video signal being corrected so that the brightness of the display, ambient brightness, and user perception characteristics are all taken into account. The brightness information may not be adjusted, or a separate adjustment method may be applied depending on the design method.

[0066] In the preceding embodiment, a case was described in which the electronic device (100) obtains two parameters, the brightness of the display at the current time and the ambient brightness, in the first correction value identification step (410), and identifies a first correction value corresponding to the two obtained parameters. However, there are not only examples in which the first correction value corresponds to both of the two parameters mentioned above. Depending on the design method, the electronic device (100) may obtain either the brightness of the display at the current time or the ambient brightness, and identify a first correction value corresponding to the obtained parameter. The operation after the first correction value is identified in this manner is as described in the preceding embodiment.

[0067] Meanwhile, depending on the design method, additional adjustments may be reflected between the brightness and color separation step (440) and the color adjustment step (450). The following describes such an embodiment.

[0068] FIG. 5 is a block diagram showing another embodiment in which an electronic device corrects the characteristics of an image.

[0069] As illustrated in FIG. 5, the electronic device (100) converts an input image signal into an output image signal and outputs it through a process of correcting the characteristics of the image. Here, the first correction value identification step (410), the user perception characteristic test step (420), the second correction value identification step (430), and the brightness and color separation step (440) are substantially the same steps as those in the embodiment of FIG. 4, so a detailed description is omitted. However, the first correction value identified in the first correction value identification step (410) is used not only in the user perception characteristic test step (420) but also in the first color adjustment step (510) to be described later.

[0070] The electronic device (100) performs a first color adjustment step (510). The electronic device (100) corrects the color information of the input image signal with a first correction value. The first correction value is Gain perceptand, in the color information of the input image signal, the saturation of one color is Cb in , Cr in When, corrected saturation Cb out , Cr out It is as follows.

[0071] Cb out =Cb in *Gain percept

[0072] Cr out =Cr in *Gain percept

[0073] In the above formula, "*" may be a multiplication symbol, or, depending on the design method, an operation symbol with various mathematical meanings. Thus, the electronic device (100) primarily adjusts the color information of the input video signal in response to the brightness of the display and the ambient brightness.

[0074] The electronic device (100) performs a brightness adjustment step (520). The brightness adjustment step (520) is applied to minimize the side effects of an increase in image brightness that may occur during the first color adjustment step (510). Depending on the design method, the brightness adjustment step (520) may not be performed if it is identified that the aforementioned side effects are negligible, thereby allowing the brightness information of the input image signal to remain unadjusted. The correction value regarding the side effects of brightness increase is Gain compress and the value of the brightness information of the input image signal is Y in , the value of the brightness information of the output video signal is Y out If so, the following relationship is satisfied.

[0075] Y out =Y in *Gain compress

[0076] Correction value Gain compress is the first correction value Gain percept It is determined according to and is arranged to have a value inversely proportional to the first correction value, thereby preventing excessive brightness enhancement due to an increase in saturation.

[0077] The electronic device (100) performs a second color adjustment step (530). The electronic device (100) applies a second correction value to the saturation of a predetermined color in the color information of the input video signal to which the first color adjustment step (510) has been applied. The color of the input video signal Hue in , the color with the second correction value reflected Hue percept If so, the color Hue of the output video signal out It is as follows.

[0078] Hue out =Hue in +Hue percept

[0079] The electronic device (100) converts an input image signal into an output image signal by combining brightness information with color information adjusted in this way.

[0080] The method for identifying the first correction value is described below.

[0081] Figure 6 is an example diagram illustrating the principle of identifying the first correction value.

[0082] As illustrated in FIG. 6, the first correction value is derived based on two parameters: display brightness and ambient brightness. In the figure, the graph on the left shows an example of a corresponding curve between display brightness and the correction value, and the graph on the right shows an example of a corresponding curve between ambient brightness and the correction value. In this embodiment, the correction values ​​corresponding to display brightness and ambient brightness, respectively, are shown as graphs, but this is merely an example. The correction values ​​corresponding to display brightness or ambient brightness, respectively, can be defined in advance in various forms, such as formulas, functions, or tables.

[0083] The curves of the two graphs show that the correction values ​​are proportional to the display brightness and ambient brightness, respectively. This is because, as the display brightness or ambient brightness increases, users perceive color saturation as lower, so the correction value for saturation must increase to compensate for this state. For example, if the correction value corresponding to display brightness x1 is y1 and the correction value corresponding to ambient brightness x2 is y2, the first correction value y can be calculated as follows.

[0084] y=W1*y1+W2*y2

[0085] W1 is a weight for display brightness, and W2 is a weight for ambient brightness. Since this formula is merely an example of one of various possible methods, the method of calculating the first correction value is not limited by this embodiment. Depending on the design method, W1 and W2 may have the same value of 1 or different values. If there is an environment where the influence of display brightness and ambient brightness on the image are almost the same, W1 and W2 may have a value of 1. If there is an environment where the influence of display brightness is greater than the influence of ambient brightness, W1 may be set to W2 > W2. Conversely, if there is an environment where the influence of ambient brightness is greater than the influence of display brightness, W1 <W2로 설정될 수 있다. 가중치의 설정은 다양한 환경적 요인을 고려하여 다양한 수치로 설정될 수 있는 사항이므로, 구체적인 수치가 한정되지 않는다.

[0086] Meanwhile, the first correction value is not calculated based on both the brightness of the display and the ambient brightness; depending on the design method, it is also possible to calculate the first correction value based on either the brightness of the display or the ambient brightness. When the first correction value y is calculated based on the brightness x1 of the display, y = W3 * y1 can be satisfied (where W3 is the weight and y1 is the correction value corresponding to the brightness x1 of the display). On the other hand, when the first correction value y is calculated based on the ambient brightness x2, y = W4 * y2 can be satisfied (where W4 is the weight and y2 is the correction value corresponding to the brightness x2 of the ambient). The weights W3 and W4 in each case can be provided as various numerical values ​​depending on the design method.

[0087] Below, examples of correction values ​​that vary by color are explained.

[0088] Figure 7 is a graph showing the curve of the correction values ​​by color.

[0089] As illustrated in FIG. 7, correction values ​​for image characteristics can be calculated for multiple colors. The human eye has different sensitivities for each color. For example, some users may be sensitive to red-based colors while being relatively insensitive to green and blue-based colors. Conversely, some users may be relatively sensitive to blue-based colors. Therefore, rather than having the same value for multiple colors, the second correction value can more accurately reflect the user's cognitive characteristics by having different values ​​for each color.

[0090] Chroma in , Chroma the saturation of the output video signal out , Gain the second correction value regarding the user's cognitive characteristics percept If so, it satisfies the relationship of the following formula.

[0091] Chroma out =Chroma in *Gainpercept

[0092] Gain percept =Gain panel *Gain environ *Gain hue

[0093] Gain panel is the saturation correction value based on display brightness, Gain environ is the saturation correction value based on ambient brightness, Gain hue represents the saturation correction value based on color. Here, depending on the design method, weights may be applied to each correction value of this formula.

[0094] Correction values ​​can be derived for multiple colors based on the user's adjustment input results for the test image as described above. However, it is not easy to derive correction values ​​for all colors that can be practically expressed in the image using the test image. Therefore, the electronic device (100) may derive correction values ​​for colors for which the user has not performed adjustment input through various techniques based on the user's adjustment input results.

[0095] As one example, the electronic device (100) derives a correction value for each of a plurality of colors, for example, seven colors h1 to h7. When considering colors h1 and h2, it is predicted that the correction value for a specific color in the h1 series will be more similar to the case of h1 than to the case of h2. In this regard, through various linear techniques, a correction value for colors between h1 and h2 that are mutually adjacent in the color spectrum can be derived. In this way, a correction value for colors between h2 and h3, h3 and h4, h4 and h5, h5 and h6, and h6 and h7 can be derived.

[0096] As another example, correction values ​​for all colors can be derived using a pre-prepared mathematical simulation or by using artificial intelligence. For example, correction values ​​for each of multiple colors h1 to h7 based on the user's adjustment input results for a test image can be applied to at least one of machine learning, neural network, or deep learning algorithms based on pre-prepared artificial intelligence.

[0097] For example, the electronic device (100) can perform the functions of both a learning unit and a recognition unit. The learning unit performs the function of generating a learned neural network, and the recognition unit performs the function of recognizing data (or inferring, predicting, estimating, or judging) using the learned neural network. The learning unit can generate or update the neural network. The learning unit can acquire learning data to generate the neural network. For example, the learning unit can acquire the learning data from the storage unit of the electronic device (100) or from an external source. The learning data may be data used for training the neural network, and the neural network can be trained using the data that has performed the above-mentioned operation as learning data.

[0098] The learning unit may perform preprocessing on the acquired training data or select data to be used for training from among multiple training data before training a neural network using the training data. For example, the learning unit may process the training data into a pre-set format, filter it, or add / remove noise to process it into a form suitable for training. The learning unit may generate a neural network configured to perform the above operations using the preprocessed training data.

[0099] A trained neural network may be composed of multiple neural networks (or layers). The nodes of the multiple neural networks have weights, and the multiple neural networks may be connected to each other such that the output value of one neural network is used as the input value of another neural network. Examples of neural networks may include models such as CNN (Convolutional Neural Network), DNN (Deep Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network), and Deep Q-Networks.

[0100] Meanwhile, the recognition unit may acquire target data to perform the above-mentioned operation. The target data may be acquired from a storage unit of the electronic device (100) or from an external source. The target data may be data to be recognized by the neural network. Before applying the target data to the trained neural network, the recognition unit may perform preprocessing on the acquired target data or select data to be used for recognition from among a plurality of target data. For example, the recognition unit may process the target data into a preset format, filter it, or add / remove noise to process it into a form of data suitable for recognition. By applying the preprocessed target data to the neural network, the recognition unit may acquire an output value output from the neural network. Along with the output value, the recognition unit may acquire a probability value or a confidence value.

[0101] Meanwhile, saturation correction values ​​based on display brightness, ambient brightness, or color can be defined in advance, and various methods are possible. Below, some of the various examples of preparing the aforementioned saturation correction values ​​in advance are described.

[0102] Figure 8 is an example diagram illustrating the principle of determining saturation correction values ​​according to display brightness through a perception experiment.

[0103] As illustrated in FIG. 8, a perception experiment to determine a saturation correction value according to display brightness may be performed in advance. In the embodiment related to FIG. 6 above, a case in which a first correction value is derived based on a saturation correction value according to display brightness and a saturation correction value according to ambient brightness was described; among these, a perception experiment to determine a saturation correction value according to display brightness is described.

[0104] For example, two displays (810, 820) with the same maximum brightness performance are provided, and an image (811, 821) of the same color is displayed on each display (810, 820). At this time, one display (820) is set to display the image (821) at maximum brightness, while the other display (810) is set to display the image (811) at a brightness lower than the maximum brightness, for example, at 70% of the maximum brightness. In this case, due to the color wash-out phenomenon, a phenomenon occurs in which the saturation of the image (821) displayed on the display (820) set to maximum brightness is perceived as low.

[0105] In this state, the display (810) set to 70% of the maximum brightness level is maintained, while the image (821) displayed on the display (820) set to the maximum brightness level is provided to the subjects with the saturation of the image (821) gradually increasing. Here, the subjects are asked to select the image (821) displayed on the maximum brightness display (820) that has a saturation that appears most similar to the saturation of the image (810) displayed on the display (810) at 70% brightness. The above experiment is conducted while varying the brightness of the displays (810, 820) so that experimental data is accumulated.

[0106] Based on accumulated experimental data, a correction value can be derived to prevent the color wash-out phenomenon that occurs depending on the display brightness.

[0107] Meanwhile, in addition to the method described above, a method for deriving correction values ​​using a Color Appearance Model (CAM) is possible. CAM is a formula-based model developed as a method for quantifying perceived colors. By applying this model, the perceived saturation can be identified according to brightness, and the amount of saturation that decreases as brightness increases can be calculated inversely.

[0108] Saturation correction value S when using the CIELAB model ab It is as follows.

[0109] S ab =[C * / (√(C *2 +L *2 ))](100%), C * =√(a *2 +b *2 )

[0110] L * is the lightness of CIELAB coordinate, a * and b * is the color coordinate of CIELAB (a *: green to red, b * :blue to yellow), C * is the chromaticity of CIELAB (from a * and b * Each represents ).

[0111] Assuming there is a 1,000 nit (1 Knit) display and a 500 nit display, the color correction value k for the 1,000 nit display to have the same saturation as the 500 nit display can be calculated as follows.

[0112] Sat 1k =C 1k / (√(C 1k 2 +L 1k 2 )), Sat 500 =C 500 / (√(C 500 2 +L 500 2 ))

[0113] Sat 1k_new =kC 1k / (√(k 2 C 1k 2 +L 1k 2 ))=Sat 500

[0114] k=(C 500 L 1k ) / (L 500 C 1k )

[0115] A correction value k can be calculated for each pixel value. The above method is merely one example among various ways to derive correction values ​​using formulas.

[0116] Figure 9 is an example diagram illustrating the principle of determining saturation correction values ​​according to ambient brightness through a perception experiment.

[0117] As illustrated in FIG. 9, a perception experiment to determine a saturation correction value based on ambient brightness may be performed in advance. In the embodiment related to FIG. 6 above, a case was described in which a first correction value is derived based on a saturation correction value based on display brightness and a saturation correction value based on ambient brightness; among these, a perception experiment to determine a saturation correction value based on ambient brightness is described.

[0118] For example, two displays (910, 920) with the same maximum brightness performance are provided, and an image (911, 921) of the same color is displayed on each display (910, 920). Here, one display (910) displays the image (911) in a dark room environment, while the other display (920) displays the image (921) in an environment where ambient brightness is increased, such as by turning on a light. In this case, due to the color wash-out phenomenon, a phenomenon occurs in which the saturation of the image (921) displayed on the display (920) is perceived as low.

[0119] In this state, the saturation of the image (921) displayed on the display (920) under an ambient environment with relatively high ambient brightness is gradually increased and provided to the subjects. Here, the subjects are asked to select the image (921) displayed on the display (920) with relatively high ambient brightness that has a saturation that appears most similar to the saturation of the image (910) displayed on the display (910) with relatively low ambient brightness. The above experiment is conducted while varying the ambient brightness so that experimental data is accumulated.

[0120] Based on accumulated experimental data, a correction value can be derived to prevent the color wash-out phenomenon that occurs depending on ambient brightness.

[0121] Meanwhile, saturation correction values ​​for each color can also be established through perception experiments. The extent to which changes in display brightness and ambient brightness cause users to perceive colors differently varies by color. Typically, the degree of color perception distortion is greater in intermediate colors than in colors close to primary colors. To reflect this tendency in the correction values, different saturation correction values ​​for each color can be determined through tests conducted for various colors when performing perception experiments related to display brightness and ambient brightness.

[0122] Below, an example of performing a user cognitive characteristics test is described.

[0123] Figure 10 is an example diagram showing an electronic device performing a user cognitive characteristic test.

[0124] As illustrated in FIG. 10, the electronic device (100) conducts a test to identify the individual user's cognitive characteristics, for example, cognitive characteristics regarding the color-specific saturation of an image. During the test, the electronic device (100) [uses] the identified first correction value Gain for a predefined default value. percept The test video reflecting this will be used. First correction value Gain percept Regarding this, it is as described in the preceding embodiment (see the embodiment related to FIG. 5). The electronic device (100) is R, which is the signal value of the test image. in , G in , B in is the YCbCr signal Y in , Cb in , Cr in Convert to, and the first correction value Gain to the CbCr signal percept Applying Cb out , Cr out It calculates. The electronic device (100) is Y in Brightness correction value Gain based on saturation compensation compress Brightness information Y with applied outBy obtaining, a YCbCr output signal is constructed in which the perceived saturation according to the display environment is compensated. The electronic device (100) converts the YCbCr output signal into an RGB signal to obtain the signal R of the final test image. test , G test , B test Obtains. The above content can be expressed as a formula as follows.

[0125] (Y in , Cb in , Cr in )=RGBtoYCbCr(R in , G in , B in )

[0126] Y out =Y in *Gain compress

[0127] Cb out =Cb in *Gain percept

[0128] Cr out =Cr in *Gain percept

[0129] (R test , G test , B test )=YCbCrtoRGB(Y out , Cb out , Cr out )

[0130] In the above formula, RGBtoYCbCr is a function that converts RGB signals to YCbCr signals, and YCbCrtoRGB is a function that converts YCbCr signals to RGB signals.

[0131] The electronic device (100) displays the test image generated in this manner on the screen. For example, the electronic device (100) displays a test image of the same color on a screen divided into 9 sections, but displays the color saturation of one section (e.g., section 3 in the present drawing) differently from the saturation of the remaining sections. The electronic device (100) allows the user to select the section that is perceived differently from the test image displayed in this manner through the user input unit (130). For example, when the screen is divided into 9 sections, each section is numbered from 1 to 9. If the user perceives the saturation of section 3 to be different, the user presses button 3 among the number buttons provided in the user input unit (130). If the saturation of all sections is perceived to be the same, the user presses button 0 among the number buttons of the user input unit (130). In addition to this, various other user input methods may be provided.

[0132] The electronic device (100) adds a score for the corresponding color when the user's selection received through the user input unit (130) is the correct answer. The electronic device (100) performs this test repeatedly several times by adjusting the saturation value differently and changing the position of the divided area with different saturation.

[0133] The electronic device (100) can obtain a user's perception score for each of the multiple colors by performing the above-mentioned test on several predefined colors.

[0134] Meanwhile, a set of test videos for testing users' cognitive characteristics set To construct this, the HSV color domain can be utilized. To construct a set of various colors, Hue can be divided into equal intervals; for example, when applying a division of 6, the representative set of colors Hue set It is as follows.

[0135] Hue set={0°, 60°, 120°, 180°, 240°, 300°}

[0136] If the Saturation and Value values ​​for the test images are too small or too large, cognitive discrimination may be reduced; therefore, for example, an intermediate value of around 0.5 may be used. To increase the number of test stages, Saturation and Value values ​​that differ for each Hue may also be used. Assuming these values ​​are applied as 0.5, the final set of test images can be expressed as follows.

[0137] Test set ={(H1, S1, V1=0°, 0.5, 0.5), (H2, S2, V2=60°, 0.5, 0.5), ... (H6, S6, V6=300°, 0.5, 0.5)}

[0138] For these six representative colors, the electronic device (100) performs a perception characteristic test in the manner described above. The electronic device (100) divides the screen into nine sections, and in eight of the divided areas, Test set Display the test image based on, and in the remaining split area, display the adjusted test image with the offset applied to the saturation value. Test set For each color, multiple tests are conducted, but the user's perception is tested by gradually decreasing the intensity of the offset of the saturation value.

[0139] When a user makes an accurate selection in the test, a discrimination score is assigned, which can be assigned, for example, inversely proportional to the size of the offset of the Saturation value. Since a smaller offset requires the user to distinguish segmented areas with saturation close to other segmented areas, the system is designed so that a higher discrimination score is assigned when the user makes an accurate distinction. In this way, Test setA cognitive characteristic test is conducted for each color, and the electronic device (100) has a color discrimination score. set Acquires.

[0140] Meanwhile, the electronic device (100) obtains the score set Based on this, color correction suitable for the user's cognitive characteristics is performed. The electronic device (100) Score set Colors where the user's color discrimination ability is relatively weak Hue min After finding it, Hue min Score, the sum of the discrimination scores of colors belonging to the left side when using the reference axis left The sum of the discrimination scores of the colors belonging to the right side Score right The electronic device (100) calculates the Hue among the colors on the same side when adding values. min Weights are assigned to colors that are closer to the value, thereby increasing the influence of the discrimination score of the corresponding color. The electronic device (100) is the calculated Score left and Score right Among them, the larger value Score max Using, the user's perceived color correction value Hue percept Produces.

[0141] Hue percept =Hue offset , if Score left < Score right

[0142] Hue percept =-Hue offset , if Score left Score right

[0143] Hue offset Score max It is determined in proportion to Hue. percept In the second color adjustment step (530, see FIG. 5) of the preceding embodiment, the color Hue of the input image signal in Hue minFor colors within the color range, the following color correction is performed.

[0144] Hue out =Hue in +Hue percept

[0145] According to this method, the electronic device (100) can convert an input video signal into an output video signal by reflecting the user's cognitive characteristics, for example, the ability to perceive saturation for each color. Since the above method is merely one example of various methods by which the electronic device (100) can reflect the user's cognitive characteristics in the video signal, this embodiment does not limit the operation of the electronic device (100) according to the concept of the present invention.

[0146] For example, the electronic device (100) may display a UI that allows the user to directly input a correction value for color-specific saturation, and may receive input through the UI. The UI may be configured to allow the input of saturation values ​​as numerical values, or may include an adjustment menu in the form of a slider bar that allows for the adjustment of saturation.

[0147] The embodiment described above relates to a case where the electronic device (100) identifies a single user and considers the cognitive characteristics of the identified user. However, there may be multiple users using the electronic device (100), and the user may vary depending on the time of use of the electronic device (100). Considering such cases, the electronic device (100) manages image cognitive characteristic correction values ​​for each user, and such an embodiment is described below.

[0148] FIG. 11 is a block diagram illustrating the principle of an electronic device managing and applying image perception characteristic correction values ​​for each user.

[0149] As illustrated in FIG. 11, the processor (160) of the electronic device (100) can store a correction value corresponding to a specific user's cognitive characteristics in the storage unit (140), and each correction value is stored to correspond to a plurality of users, thereby forming a DB (1100). When the electronic device (100) derives a correction value corresponding to the user's cognitive characteristics while the user is identified, it stores the derived correction value in the DB (1100) to correspond to the identified ID of the user. Since the method for deriving the correction value has been described in the preceding embodiment, a detailed description is omitted.

[0150] There are various ways for the processor (160) to identify a user, and it is not limited to any one of them. For example, the processor (160) may receive user ID information entered by the user through the user input unit (130) to perform a login, and identify the user when the login is successfully performed. Alternatively, the processor (160) may also receive user ID information through the interface unit (120). Alternatively, the processor (160) may receive an image of the user captured by a sensor (150) implemented as a camera, and identify the user ID within the image through image analysis.

[0151] The processor (160) searches for a correction value corresponding to the identified user ID in the DB (1100). If a correction value corresponding to the user ID is not found in the DB (1100), the processor (160) may perform a user cognitive characteristic test as described in the preceding embodiment. If a correction value corresponding to the user ID is found in the DB (1100), the processor (160) displays an image reflecting the found correction value.

[0152] Meanwhile, there may be a difference in the environment between the first point in time when a correction value is derived considering the user's cognitive characteristics and the second point in time when the image is displayed reflecting the correction value. That is, there may be a difference between the brightness of the display or ambient brightness at the first point in time and the brightness of the display or ambient brightness at the second point in time. For example, if the indoor light is changed to a brighter one after the first point in time, the image is displayed at the second point in time under an environment where the ambient brightness has increased compared to the first point in time. Taking this into consideration, the electronic device (100) may perform additional adjustments to the correction value, and such an embodiment is described below.

[0153] FIG. 12 is a flowchart illustrating the process of an electronic device adjusting a correction value in response to environmental changes.

[0154] As illustrated in FIG. 12, the following operation is performed by a processor (160, see FIG. 2) of an electronic device.

[0155] In step 1210, the electronic device derives and stores a correction value regarding the user's cognitive characteristics. The method for deriving the correction value is as described in the preceding embodiment.

[0156] In step 1220, the electronic device detects an image display event.

[0157] In step 1230, the electronic device identifies the user currently using the electronic device.

[0158] In step 1240, the electronic device calculates the difference between the value of the display environment at the time of deriving the correction value corresponding to the identified user and the value of the display environment at the current time. For example, the electronic device can calculate the difference between the display brightness at the time of deriving the correction value and the display brightness at the current time, and the difference between the ambient brightness at the time of deriving the correction value and the ambient brightness at the current time.

[0159] In step 1250, the electronic device identifies whether the calculated difference value is greater than the threshold value.

[0160] If it is identified that the calculated difference value is greater than the threshold value ("Yes" in step 1250), in step 1260, the electronic device reflects a predefined offset value corresponding to the calculated difference value into the correction value. This offset value may be defined in advance by experiments, simulations, etc., or determined according to a function or formula. For example, if the difference regarding display brightness does not exceed a predetermined first threshold value and the difference regarding ambient brightness exceeds a predetermined second threshold value, the electronic device may reflect an offset value corresponding to the difference value of ambient brightness into the correction value.

[0161] In step 1270, the electronic device displays a corrected image according to the correction value.

[0162] On the other hand, if it is identified that the calculated difference value is not greater than the threshold value ("No" at step 1250), the electronic device proceeds to step 1270. That the difference value is not greater than the threshold value means that there is a difference between the two display environments, but the difference is not significant enough to be meaningful.

[0163] The operation of the device as described in the above embodiments may be performed by artificial intelligence installed in the device. Artificial intelligence can be applied to various systems by utilizing machine learning algorithms. An artificial intelligence system is a computer system that implements intelligence at a human level or comparable to a human level, in which a machine, device, or system autonomously learns and makes judgments, and in which recognition rates and judgment accuracy improve based on the accumulation of usage experience. Artificial intelligence technology consists of machine learning technologies that utilize algorithms to self-classify and learn the characteristics of input data, and elemental technologies that mimic functions such as cognition and judgment of the human brain by utilizing such algorithms.

[0164] The elemental technologies include, for example, at least one of linguistic understanding technology that recognizes human language and characters, visual understanding technology that perceives objects like human vision, reasoning and prediction technology that judges information to logically reason and predict, knowledge representation technology that processes human experience information into knowledge data, and motion control technology that controls the autonomous driving of vehicles or the movement of robots.

[0165] Here, linguistic understanding refers to the technology of recognizing and applying human language or text, including natural language processing, machine translation, dialogue systems, question answering, speech recognition, and synthesis.

[0166] Inference prediction is a technology that makes logical predictions by judging information, and includes knowledge and probability-based inference, optimization prediction, preference-based planning, and recommendation.

[0167] Knowledge representation is a technology that automates the processing of human experiential information into knowledge data, and includes knowledge construction such as data generation and classification, and knowledge management such as data utilization.

[0168] Methods according to exemplary embodiments of the present invention may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. Such a computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. For example, the computer-readable medium may be stored in a non-volatile storage device such as a USB memory device, regardless of whether it is erasable or rewritable, or in a memory such as, for example, RAM, ROM, flash memory, memory chip, integrated circuit, or a storage medium that is optically or magnetically writable and simultaneously machine-readable (e.g., computer), such as, for example, CD, DVD, magnetic disk, or magnetic tape. It will be understood that memory included in a mobile terminal is an example of a machine-readable storage medium suitable for storing a program or programs containing instructions for implementing embodiments of the present invention. The program instructions recorded on the storage medium may be those specifically designed and configured for the present invention, or may be those known and available to a person skilled in the art of computer software. Alternatively, the computer program instructions may be implemented by a computer program product. Explanation of the symbols

[0169] 100 : Electronic device 110: Display section 120 : Interface section 130 : User Input Section 140 : Storage section 150 : Sensor 160 : Processor

Claims

Claim 1 An electronic device comprising: a display; and a processor that identifies an image display environment including the brightness of the display, corrects the characteristics of a test image provided to identify user visibility regarding the characteristics of the image to correspond to the identified display environment, controls the corrected test image to be displayed on the display, and corrects the characteristics of the image based on user adjustment input regarding the characteristics of the displayed test image, wherein the processor identifies a predefined correction value proportional to the brightness of the display and reflects the identified correction value in the value of the characteristics of the test image. Claim 2 delete Claim 3 In claim 1, the processor is an electronic device that corrects the saturation of each color of the test image. Claim 4 delete Claim 5 An electronic device according to claim 1, further comprising an interface unit for receiving a video signal, wherein the processor corrects the characteristics of the video by reflecting together the correction value and the second correction value based on the adjustment input in the color information of the video signal received through the interface unit. Claim 6 In paragraph 5, the processor is an electronic device that reflects a pre-defined third correction value inversely proportional to the correction value to the brightness information of the image signal received through the interface unit. Claim 7 In claim 1, the processor is an electronic device that calculates a predefined correction value proportional to the brightness of the display by summing a correction value corresponding to the brightness of the display and a correction value corresponding to the ambient brightness of the electronic device. Claim 8 In claim 7, the processor is an electronic device that calculates a predefined correction value proportional to the brightness of the display by assigning different weights to each of the correction value corresponding to the brightness of the display and the correction value corresponding to the ambient brightness. Claim 9 An electronic device according to claim 1, further comprising an interface unit for receiving a video signal, wherein the processor corrects the characteristics of the video by reflecting a second correction value based on the adjustment input to the color information of the video signal received through the interface unit. Claim 10 In claim 9, the test image comprises a plurality of divided regions having the same color, and one of the plurality of regions has a different saturation from the remaining regions, and the processor is an electronic device that measures a user's score for the color in response to whether the adjustment input normally selects the region with the different saturation, and derives the second correction value based on the measured score. Claim 11 An electronic device according to claim 1, further comprising a storage unit for storing a second correction value corresponding to a user, wherein the processor acquires the second correction value stored in the storage unit when displaying the image, and adjusts the second correction value based on the difference between the display environment at the time of derivation of the second correction value and the display environment at the current time. Claim 12 A method for controlling an electronic device, comprising: a step of identifying an image display environment including the brightness of a display of the electronic device; a step of correcting the characteristics of a test image provided to identify user visibility regarding the characteristics of the image to correspond to the identified display environment; a step of controlling the corrected test image to be displayed on the display; and a step of correcting the characteristics of the image based on user adjustment input regarding the characteristics of the displayed test image, wherein the step of correcting the characteristics of the test image includes identifying a predefined correction value proportional to the brightness of the display and reflecting the identified correction value in the value of the characteristics of the test image. Claim 13 delete Claim 14 In claim 12, the step of correcting the characteristics of the image is a control method of an electronic device that corrects the saturation of each color of the test image. Claim 15 delete Claim 16 In claim 12, the step of correcting the characteristics of the image comprises a method for controlling an electronic device that corrects the characteristics of the image by reflecting together the correction value and a second correction value based on the adjustment input in the color information of the image signal. Claim 17 In claim 16, the step of correcting the characteristics of the image comprises a step of reflecting a third correction value, which is predefined to be inversely proportional to the correction value, into the brightness information of the image signal, in a control method of an electronic device. Claim 18 In claim 12, the step of correcting the characteristics of the test image comprises a step of calculating a pre-defined correction value proportional to the brightness of the display by summing a correction value corresponding to the brightness of the display and a correction value corresponding to the ambient brightness of the electronic device. Claim 19 In claim 18, the step of correcting the characteristics of the test image comprises a method for controlling an electronic device, wherein different weights are assigned to each of the correction value corresponding to the brightness of the display and the correction value corresponding to the ambient brightness to calculate the previously defined correction value proportional to the brightness of the display. Claim 20 In claim 12, the step of correcting the characteristics of the image is a control method of an electronic device that corrects the characteristics of the image by reflecting a second correction value based on the adjustment input into the color information of the image signal.

Images