Image processing method and device, electronic equipment and storage medium
By obtaining adjustment parameters and correction curves, the target adjustment curve is determined to correct the pixel output value of the basic curve, the channel coupling and numerical truncation problems of highlight and shadow adjustment in image processing are solved, and the local brightness adjustment effect is improved.
Patent Information
- Application Number
- CN202410096241.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-01-23
- Publication Date
- 2025-07-25
AI Technical Summary
The existing highlight and shadow adjustment methods have problems with channel coupling influence and numerical truncation in image processing, resulting in poor local brightness adjustment effect.
By obtaining adjustment parameters, determine the target adjustment curve in the candidate adjustment curve set, use the correction curve to correct the pixel output value of the basic curve, determine the target pixel value based on the target adjustment curve to generate the target image, and ensure that the brightness of the highlights and shadow areas conforms to the actual state.
This improves the problem of excessive brightness changes in the highlight area due to channel coupling, avoids numerical truncation of the highlight area, and improves the local brightness adjustment effect.
Smart Images
Figure CN120374471A_ABST
Abstract
Description
Technical Field
[0001] Embodiments of the present disclosure relate to image technology, and in particular, to an image processing method, apparatus, electronic device, and storage medium. Background Art
[0002] In the field of image processing, highlights represent bright regions in an image, and shadows represent dark regions in an image. By adjusting the highlights and shadows of an image, the local brightness of the image can be adjusted.
[0003] Currently, some methods for adjusting highlights and shadows may have a coupling effect between channels, resulting in a large change in the highlight region of the image when adjusting the shadow region of the image. There are also some adjustment methods that truncate values in the highlight region of the image to meet the adjustment algorithm, thereby causing loss of image information. Therefore, the current methods for adjusting highlights and shadows have the problem of poor local brightness adjustment effect. Summary of the Invention
[0004] The present disclosure provides an image processing method, apparatus, electronic device, and storage medium, which can make the change range of the highlight region or the shadow region meet the adjustment requirements and improve the local brightness adjustment effect.
[0005] In a first aspect, an embodiment of the present disclosure provides an image processing method, including:
[0006] Obtaining an original image and adjustment parameters, where the adjustment parameters have a mapping relationship with candidate adjustment curves in a candidate adjustment curve set, the candidate adjustment curves include a basic curve and a correction curve, and the correction curve is used to correct the pixel output value of the basic curve;
[0007] Obtaining a target adjustment curve in the candidate adjustment curve set according to the adjustment parameters;
[0008] Determining a target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determining a target image according to the target pixel value, where the target pixel value represents the corrected pixel output value.
[0009] In a second aspect, an embodiment of the present disclosure further provides an image processing apparatus, including:
[0010] A parameter acquisition module, configured to obtain an original image and adjustment parameters, where the adjustment parameters have a mapping relationship with candidate adjustment curves in a candidate adjustment curve set, the candidate adjustment curves include a basic curve and a correction curve, and the correction curve is used to correct the pixel output value of the basic curve;
[0011] A curve acquisition module, configured to obtain a target adjustment curve in the candidate adjustment curve set according to the adjustment parameters;
[0012] An image determination module, configured to determine a target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determine a target image according to the target pixel value, where the target pixel value represents a corrected pixel output value.
[0013] In a third aspect, an embodiment of the present disclosure further provides an electronic device, where the electronic device includes:
[0014] One or more processors;
[0015] A storage device for storing one or more programs,
[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the image processing method as described in any embodiment of the present disclosure.
[0017] In a fourth aspect, an embodiment of the present disclosure further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are used to execute the image processing method as described in any embodiment of the present disclosure when executed by a computer processor.
[0018] An embodiment of the present disclosure provides an image processing method, apparatus, electronic device, and storage medium. By adjusting parameters, a corresponding target adjustment curve is determined from a candidate adjustment curve set. According to the target adjustment curve, a target pixel value is determined based on the original pixel value of the original image. Then, according to the target pixel value, a target image is determined. Since the target pixel value is obtained by correcting the pixel output value of the base curve based on the correction curve, and the target image is determined based on the target pixel value, the brightness of the target image in the shadow area and the highlight area is more in line with the actual brightness state, improving the problem that the highlight changes greatly when adjusting the shadow due to inter-channel coupling, and also avoiding the numerical truncation in the highlight area. The change amplitude in the highlight area or the shadow area can meet the adjustment requirements, improving the local brightness adjustment effect. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] Combined with the accompanying drawings and referring to the following specific embodiments, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more obvious. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic, and the original and elements are not necessarily drawn to scale.
[0020] Figure 1 It is a flowchart of an image processing method provided by an embodiment of the present disclosure;
[0021] Figure 2 It is a schematic diagram of an interactive interface provided by an embodiment of the present disclosure;
[0022] Figure 3 A comparison diagram of the adjustment effects of a target adjustment curve, a basic curve, and a baseline provided by an embodiment of the present disclosure;
[0023] Figure 4 Another comparison diagram of the adjustment effects of a target adjustment curve, a basic curve, and a baseline provided by an embodiment of the present disclosure;
[0024] Figure 5 A schematic structural diagram of an image processing device provided by an embodiment of the present disclosure;
[0025] Figure 6 A schematic structural diagram of an electronic device provided by an embodiment of the present disclosure. Detailed implementation manners
[0026] Embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.
[0027] It should be understood that the various steps recorded in the method embodiments of the present disclosure can be executed in different orders and / or executed in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.
[0028] As used herein, the term "including" and its variants are open-ended, that is, "including but not limited to". The term "based on" is "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.
[0029] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or mutual dependence relationship of the functions executed by these devices, modules or units.
[0030] It should be noted that the modifications of "one" and "plural" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".
[0031] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are for illustrative purposes only and are not used to limit the scope of these messages or information.
[0032] It can be understood that the data involved in the technical solution (including but not limited to the data itself, the acquisition or use of the data) should comply with the requirements of the corresponding laws, regulations and related provisions.
[0033] Figure 1 The following is a schematic flowchart of an image processing method provided by an embodiment of the present disclosure. The embodiment of the present disclosure is applicable to the case of local brightness adjustment. This method can be executed by an image processing device, which can be implemented in the form of software and / or hardware. Optionally, it is implemented by an electronic device, which can be a mobile terminal, a PC or a server, etc.
[0034] As Figure 1 shown, the method includes:
[0035] S110. Obtain an original image and adjustment parameters.
[0036] Among them, the adjustment parameters have a mapping relationship with the candidate adjustment curves in the candidate adjustment curve set. The candidate adjustment curves include a base curve and a correction curve, and the correction curve is used to correct the pixel output value of the base curve.
[0037] The correction curve represents a curve whose pixel output value is positive after passing through the target coordinate point and within the target interval. The target interval represents a numerical interval determined based on the abscissa of the target coordinate point. Among them, the target coordinate point can be a preset coordinate point. For example, the target coordinate points can include (0, 0) and (1, 0), representing the minimum brightness value and the maximum brightness value respectively. The target interval can be the [0, 1] interval, and by adjusting the coefficients of the correction curve, it can be ensured that the pixel output value of the correction curve within the [0, 1] interval is greater than 0. In some embodiments, the correction curve can represent a continuous curve passing through the points (0, 0) and (1, 0) and having a pixel output value greater than 0 within the [0, 1] interval.
[0038] In some embodiments, the correction method of the correction curve includes: for the original pixel value in the original image, determine the pixel correction value corresponding to the correction curve and the original pixel value; based on the pixel correction value, correct the pixel output value output by the base curve based on the original pixel value, so as to correct the deviation between the pixel output value of the base curve and the original pixel value.
[0039] For example, for the original pixel values in the original image, the original pixel values are used as the input parameters of the correction curve, and the pixel correction values calculated by the correction curve based on the input parameters are obtained. The original pixel values are used as the input parameters of the base curve, and the pixel output values calculated by the base curve based on the input parameters are obtained. The pixel correction values are superimposed on the pixel output values to obtain the corrected pixel output values, that is, the target pixel values.
[0040] For example, the adjustment parameters and the curve coefficients of the candidate adjustment curve form mapping data. The corresponding adjustment parameters can be determined through the adjustment event for the target control in the interaction interface.
[0041] Among them, the target control represents the candidate adjustment control to be adjusted in the candidate control set. The candidate control set includes an acquisition control and candidate adjustment controls. The candidate adjustment controls include a dark part adjustment control and a bright part adjustment control. The dark part adjustment control is used to adjust the brightness of the shadow area in the image. The bright part adjustment control is used to adjust the brightness of the highlight area in the image.
[0042] For example, if the slider on the dark part adjustment control is slid, the dark part adjustment parameter is determined according to the slider position. If the slider on the bright part adjustment control is slid, the bright part adjustment parameter is determined according to the slider position.
[0043] In some embodiments, the candidate adjustment control can be a progress bar control, and by default, the slider is located at the middle position of the bottom rail area. When the slider is located at the middle position of the bottom rail area, the adjustment parameter is the default value, indicating that the original pixel value is not adjusted. At this time, the target pixel value is equal to the original pixel value. Starting from the middle position, the slider is slid left and right along the bottom rail area, and different positions of the slider correspond to different adjustment parameters, so as to adjust the original pixel value based on the target adjustment curve corresponding to the adjustment parameter to obtain the target pixel value.
[0044] The acquisition control is used to trigger the acquisition event of the original image. The original image can be an image to be locally brightness-adjusted. The original image can be a picture or video stored locally, or it can also be a currently captured picture or video, etc. If the original image is a video, local brightness adjustment needs to be performed frame by frame on the video.
[0045] The candidate adjustment curve set can be a set of candidate adjustment curves. The mapping relationship between the curve coefficients of the candidate adjustment curves and the adjustment parameters is determined in advance, and the mapping relationship between the curve coefficients and the adjustment parameters can be updated according to the adjustment accuracy. For example, currently, the adjustment parameters are set in steps of 0.2. For scenarios with higher adjustment accuracy, the adjustment parameters may be set in steps of 0.1. It is necessary to re-determine the mapping relationship between the new adjustment parameters and the curve coefficients.
[0046] Optionally, the mapping relationship between the adjustment parameter and the curve coefficient can be determined by data fitting. For example, for a preset adjustment parameter, in combination with the desired curve shape, the curve coefficient in the curve formula is adjusted to obtain a set of mapping data between the adjustment parameter and the curve coefficient. The mapping relationships between all adjustment parameters and curve coefficients are established in the above manner to obtain multiple sets of mapping data between the adjustment parameter and the curve coefficient. The multiple sets of mapping data are fitted by data fitting to obtain a relational expression with the adjustment parameter as the independent variable and the curve coefficient as the dependent variable.
[0047] The basic curve represents the mapping relationship between the original pixel values and the pixel output values of the image. For example, the curve formula of the basic curve may include a standard exponential formula, and the dark part change range of the standard exponential formula is larger than the bright part change range. Among them, the dark part represents the shadow area, and the bright part represents the highlight area.
[0048] Exemplarily, the obtaining of the adjustment parameter includes: displaying a candidate control set in the interaction interface, the candidate control set including candidate adjustment controls, where the candidate adjustment controls include a dark part adjustment control and a bright part adjustment control; obtaining an adjustment event for a target control in the candidate adjustment controls, the adjustment event including the identification information and status information of the target control, and determining the adjustment parameter according to the identification information and status information.
[0049] Among them, the identification information is used to represent the target control corresponding to the adjustment event. For example, the identification information can represent that the target control corresponding to the adjustment event is a dark part adjustment control or a bright part adjustment control. The status information can represent the slider displacement of the dark part adjustment control or the slider displacement of the bright part adjustment control, and the adjustment degree of the shadow area or the highlight area in the image is represented by the slider displacement.
[0050] Optionally, the candidate control set further includes an acquisition control, and in response to a click event for the acquisition control, the original image is acquired.
[0051] Figure 2 A schematic diagram of an interaction interface provided by an embodiment of the present disclosure. As Figure 2 shown, the interaction interface includes an image display area 210 and a candidate control set. The candidate control set includes an acquisition control 220 and candidate adjustment controls 230. The candidate adjustment controls 230 include a dark part adjustment control 231 and a bright part adjustment control 232. Obtaining a click event for the acquisition control 220 triggers an image loading event, acquires the original image 240, and displays the original image 240 in the image display area 210. If a sliding operation on the slider of the dark part adjustment control 231 is obtained, a shadow adjustment event is triggered. If a sliding operation on the slider of the bright part adjustment control 232 is obtained, a highlight adjustment event is triggered.
[0052] If the identification information and slider displacement of the dark part adjustment control 231 included in the shadow adjustment event are obtained, the adjustment parameters in the shadow adjustment scenario are determined by combining the identification information and the slider position. Alternatively, if the identification information and slider displacement of the bright part adjustment control 232 included in the highlight adjustment event are obtained, the adjustment parameters in the highlight adjustment scenario are determined by combining the identification information and the slider position.
[0053] S120. Obtain a target adjustment curve from the candidate adjustment curve set according to the adjustment parameters.
[0054] Among them, the target adjustment curve represents the candidate adjustment curve corresponding to the adjustment parameters in the candidate adjustment curve set. The candidate adjustment curve set includes a dark part adjustment curve group and a bright part adjustment curve group, and the bright part adjustment curve group is obtained by rotating the dark part adjustment curve in the dark part adjustment curve group by a set angle with a set coordinate point as the rotation center.
[0055] In some embodiments, the dark part adjustment curve group and the bright part adjustment curve group are determined in advance to obtain a candidate adjustment curve set. Among them, the dark part adjustment curve is obtained by combining the standard exponential formula and the correction term corresponding to the correction curve. For example, in order to reduce the bright part change range, a correction term can be superimposed on the basis of the standard exponential formula, and the correction term represents the correction curve. The pixel output value of the standard exponential formula in the highlight area is corrected by the correction curve to improve the gradualness of the highlight area relative to the baseline. Among them, the baseline is the identity mapping curve, which means that no conditions are imposed on the original pixel values of the original image, and the target pixel value is equal to the original pixel value.
[0056] The curve coefficients of the dark part adjustment curve include: the exponent of the standard exponential formula and the coefficient of the correction term. Since the adjustment requirement for shadow adjustment is to adjust the dark part while minimizing the change amplitude of the bright part as much as possible. For example, the adjustment requirement for shadow adjustment is: the brightness of the dark part of the original image is adjusted, and as the brightness value increases, the change amplitude should gradually decrease, that is, the change amplitude in the bright part should gradually decrease. The change range of the standard exponential formula in the dark part is greater than that in the bright part, but the change in the bright part is still large, which is different from the adjustment requirement. Therefore, it is necessary to correct the standard exponential formula in combination with the correction term to reduce the change amplitude of the bright part when adjusting the dark part.
[0057] For example, in the shadow adjustment scenario, multiple groups of mapping data between the adjustment parameters and the curve coefficients include (I0, a0, b0), (I1, a1, b1), (I2, a2, b2), (I3, a3, b3), (I4, a4, b4), (I5, a5, b5), (I6, a6, b6), ……, (I n , a n , b n ), where n represents the number of groups of mapping data, and I iRepresents the adjustment parameter, a i and b i represent the curve coefficients. By using the data fitting method, the relationships between I and a, and between I and b are obtained respectively. Thus, after knowing each adjustment parameter, according to the relationships between I and a, and between I and b, the target coefficients a and b corresponding to the current adjustment parameter are calculated respectively. Then, in combination with a, b, and the dark part adjustment curve formula, the dark part adjustment curve corresponding to the current adjustment parameter is determined. The dark part adjustment curves corresponding to each adjustment parameter are determined in the same way. The dark part adjustment curve group is formed according to the dark part adjustment curves.
[0058] Figure 3 This is a comparison diagram of the adjustment effects of a target adjustment curve, a basic curve, and a baseline provided by an embodiment of the present disclosure. As Figure 3 shown, the baseline 310 is an identity mapping curve represented by a short dashed line, the dark part adjustment curve 320 is a continuous curve represented by a long dashed line, and the basic curve 330 is a continuous curve represented by a solid line. It can be seen from Figure 3 that when the variation degrees of the basic curve 330 and the dark part adjustment curve 320 in the shadow area are similar, the dark part adjustment curve 320 is significantly closer to the baseline 310 than the basic curve 330 in the highlight area. That is, when the dark part adjustment curve 320 adjusts the shadow area, the highlight area is less affected, and the problem that the brightness change in the highlight area is too large due to channel coupling when adjusting the shadow area can be improved.
[0059] In some cases, when the variation amplitudes of the basic curve and the dark part adjustment curve in the highlight area are close, the dark part adjustment curve has a larger shadow variation range.
[0060] Figure 4 This is another comparison diagram of the adjustment effects of a target adjustment curve, a basic curve, and a baseline provided by an embodiment of the present disclosure. As Figure 4 shown, the baseline 410 is an identity mapping curve represented by a short dashed line, the dark part adjustment curve 420 is a continuous curve represented by a long dashed line, and the basic curve 430 is a continuous curve represented by a solid line. It can be seen from Figure 4 that when the variation degrees of the dark part adjustment curve 420 and the basic curve 430 in the highlight area are close, the shadow area has a larger variation range. That is, compared with the basic curve 430, the dark part adjustment curve 420 has a larger adjustment range and stronger adjustability.
[0061] Optionally, since the dark part adjustment curve and the light part adjustment curve have a rotational symmetry relationship, that is, the two types of adjustment curves have the characteristic of rotational symmetry centered on a set coordinate point. Thus, the light part adjustment curve can be determined according to the dark part adjustment curve group, and the light part adjustment curve group is formed according to the light part adjustment curve.
[0062] For example, taking the set coordinate point as the rotation center, rotate the points on the dark part adjustment curve by a set angle to obtain the points on the bright part adjustment curve. Assume any point (x, y) on the dark part adjustment curve, and the corresponding point (xˊ, yˊ) on the bright part adjustment curve after rotation. It can be expressed as xˊ = 1 - x, yˊ = 1 - y. Then, substitute xˊ and yˊ into the curve formula of the dark part adjustment curve to obtain the curve formula of the bright part adjustment curve.
[0063] Then, invert the adjustment parameter I in the shadow adjustment scenario to obtain the adjustment parameter -I in the highlight adjustment scenario. Then, let I = -I. According to the relationship between I and a, substitute I with -I, and denote the calculated a as aˊ. Similarly, according to the relationship between I and b, bˊ can be calculated. Thus, combining aˊ, bˊ and the curve formula of the bright part adjustment curve, the bright part adjustment curve is determined.
[0064] In the embodiments of the present disclosure, the curve formula of the adjustment curve can be obtained by combining the standard exponential formula and the correction term. It should be noted that for the convenience of understanding, the embodiments of the present disclosure provide a way to represent the basic curve with the standard exponential formula. However, the basic curve is not limited to being represented by the standard exponential formula, and other curves with similar properties can also be used as the basic curve. The embodiments of the present disclosure do not make specific limitations on this.
[0065] Exemplarily, according to the mapping relationship between the adjustment parameter and the curve coefficient, obtain the target curve coefficient corresponding to the adjustment parameter, and determine the target adjustment curve corresponding to the adjustment parameter according to the target curve coefficient.
[0066] In some embodiments, if the adjustment parameter is a dark part adjustment parameter, determine the dark part curve coefficient corresponding to the dark part adjustment parameter, and obtain the target dark part adjustment curve in the dark part adjustment curve group according to the dark part curve coefficient. For example, if the adjustment parameter is a dark part adjustment parameter, based on the mapping relationship between the dark part adjustment parameter and the dark part curve coefficient, determine the dark part curve coefficient corresponding to the dark part adjustment parameter, and then obtain the target dark part adjustment curve in the dark part adjustment curve group according to the dark part curve coefficient.
[0067] If the adjustment parameter is a bright part adjustment parameter, determine the bright part curve coefficient corresponding to the bright part adjustment parameter, and obtain the target bright part adjustment curve in the bright part adjustment curve group according to the bright part curve coefficient. For example, if the adjustment parameter is a bright part adjustment parameter, based on the mapping relationship between the bright part adjustment parameter and the bright part curve coefficient, determine the bright part curve coefficient corresponding to the bright part adjustment parameter, and then obtain the target bright part adjustment curve in the bright part adjustment curve group according to the bright part curve coefficient.
[0068] S130. Determine the target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determine the target image according to the target pixel value.
[0069] Among them, the target pixel value represents the corrected pixel output value.
[0070] Exemplarily, for the original pixel value of the original image, obtain the pixel output value determined by the base curve based on the original pixel value, and obtain the pixel correction value determined by the correction curve based on the original pixel value; superimpose the pixel output value and the pixel correction value to obtain the target pixel value, and use the target pixel value to update the original pixel value of the original image to obtain the target image.
[0071] The technical solution of the embodiments of the present disclosure determines the corresponding target adjustment curve from the candidate adjustment curve set by adjusting parameters, determines the target pixel value based on the original pixel value of the original image according to the target adjustment curve, and then determines the target image according to the target pixel value. Since the pixel output value of the base curve is corrected based on the correction curve to obtain the target pixel value, and the target image is determined based on the target pixel value, the brightness of the target image in the shadow area and the highlight area is more in line with the actual brightness state, improving the problem that the highlight changes greatly when adjusting the shadow due to the coupling between channels, and also avoiding the numerical truncation in the highlight area, so that the change amplitude in the highlight area or the shadow area can meet the adjustment requirements and improve the local brightness adjustment effect.
[0072] Figure 5 It is a schematic structural diagram of an image processing device provided by the embodiments of the present disclosure. The device can be implemented in the form of software and / or hardware. Optionally, it is implemented by an electronic device, and the electronic device can be a mobile terminal, a PC terminal or a server, etc.
[0073] As Figure 5 shown, the device includes: a parameter acquisition module 510, a curve acquisition module 520, and an image determination module 530.
[0074] The parameter acquisition module 510 is configured to acquire an original image and adjustment parameters, where the adjustment parameters have a mapping relationship with candidate adjustment curves in a candidate adjustment curve set, the candidate adjustment curves include a base curve and a correction curve, and the correction curve is used to correct the pixel output value of the base curve;
[0075] The curve acquisition module 520 is configured to acquire a target adjustment curve from the candidate adjustment curve set according to the adjustment parameters;
[0076] The image determination module 530 is configured to determine a target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determine a target image according to the target pixel value, where the target pixel value represents the corrected pixel output value.
[0077] Optionally, the correction curve represents a curve with positive pixel output values passing through the target coordinate point and within the target interval, and the target interval represents a numerical interval determined based on the abscissa of the target coordinate point.
[0078] Optionally, the correction method of the correction curve includes:
[0079] For the original pixel values in the original image, determine the pixel correction values corresponding to the correction curve and the original pixel values;
[0080] Based on the pixel correction values, correct the pixel output values output by the basic curve based on the original pixel values to correct the deviation between the pixel output values of the basic curve and the original pixel values.
[0081] Optionally, the candidate adjustment curve set includes a dark part adjustment curve group and a bright part adjustment curve group, and the bright part adjustment curve group is obtained by rotating the dark part adjustment curves in the dark part adjustment curve group by a set angle with a set coordinate point as the rotation center.
[0082] Optionally, the curve acquisition module 520 is specifically configured to:
[0083] If the adjustment parameter is a dark part adjustment parameter, determine the dark part curve coefficient corresponding to the dark part adjustment parameter, and obtain the target dark part adjustment curve in the dark part adjustment curve group according to the dark part curve coefficient;
[0084] Or,
[0085] If the adjustment parameter is a bright part adjustment parameter, determine the bright part curve coefficient corresponding to the bright part adjustment parameter, and obtain the target bright part adjustment curve in the bright part adjustment curve group according to the bright part curve coefficient.
[0086] Optionally, the image determination module 530 is specifically configured to:
[0087] For the original pixel values of the original image, obtain the pixel output values determined by the basic curve based on the original pixel values, and obtain the pixel correction values determined by the correction curve based on the original pixel values;
[0088] Overlay the pixel output values and the pixel correction values to obtain the target pixel values, and update the original pixel values of the original image with the target pixel values to obtain the target image.
[0089] Optionally, the parameter acquisition module 510 is specifically configured to:
[0090] Display a candidate control set in the interaction interface, where the candidate control set includes candidate adjustment controls, and among them, the candidate adjustment controls include dark part adjustment controls and bright part adjustment controls;
[0091] Obtain an adjustment event for a target control among the candidate adjustment controls, where the adjustment event includes identification information and status information of the target control, and determine the adjustment parameter according to the identification information and the status information.
[0092] The image processing device provided by the embodiments of the present disclosure can execute the image processing method provided by any embodiment of the present disclosure, and has functional modules and beneficial effects corresponding to the execution of the method.
[0093] It should be noted that the various units and modules included in the above device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the embodiments of the present disclosure.
[0094] Figure 6 It is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure. The following refers to Figure 6 , which shows a schematic structural diagram of an electronic device 600 suitable for implementing the embodiments of the present disclosure (such as Figure 6 the terminal device or server in). The terminal device in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and usage scope of the embodiments of the present disclosure.
[0095] As Figure 6 shown, the electronic device 600 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 601, which can execute various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage device 608 into the random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. The editing / output (I / O) interface 605 is also connected to the bus 604.
[0096] Typically, the following devices can be connected to the I / O interface 605: input devices 606 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and a communication device 609. The communication device 609 can allow the electronic device 600 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 6 the electronic device 600 with various devices is shown, it should be understood that it is not required to implement or have all the shown devices. Instead, more or fewer devices can be implemented or had.
[0097] In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. When the computer program is executed by the processing device 601, the above functions defined in the methods of the embodiments of the present disclosure are executed.
[0098] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.
[0099] The electronic device provided by the embodiment of the present disclosure and the image processing method provided by the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.
[0100] The embodiment of the present disclosure provides a computer storage medium, on which a computer program is stored, and when the program is executed by a processor, the image processing method provided by the above embodiment is implemented.
[0101] It should be noted that the above-mentioned computer-readable medium in the present disclosure can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable signal medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.
[0102] In some embodiments, the client and the server can communicate using any currently known or future-developed network protocol such as HTTP (HyperText Transfer Protocol), and can be interconnected with digital data communication in any form or medium (for example, a communication network). Examples of the communication network include a local area network ("LAN"), a wide area network ("WAN"), the Internet (for example, the Internet), and a peer-to-peer network (for example, an ad hoc peer-to-peer network), as well as any currently known or future-developed network.
[0103] The above-mentioned computer-readable medium can be included in the above-mentioned electronic device; or it can exist separately without being assembled into the electronic device.
[0104] The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device is caused to:
[0105] Obtain the original image and adjustment parameters, where the adjustment parameters have a mapping relationship with the candidate adjustment curves in the candidate adjustment curve set, the candidate adjustment curves include a basic curve and a correction curve, and the correction curve is used to correct the pixel output value of the basic curve;
[0106] Obtain the target adjustment curve in the candidate adjustment curve set according to the adjustment parameters;
[0107] Determine the target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determine the target image according to the target pixel value, where the target pixel value represents the corrected pixel output value.
[0108] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include, but are not limited to, object-oriented programming languages - such as Java, Smalltalk, C++; and also include conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network - including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by connecting through an Internet service provider via the Internet).
[0109] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that, in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.
[0110] The units involved in the embodiments of the present disclosure can be implemented in software or in hardware. In some cases, the name of a unit does not constitute a limitation on the unit itself.
[0111] The functions described above herein can be performed, at least in part, by one or more hardware logic components. By way of example, and without limitation, the types of hardware logic components that may be used include: Field Programmable Gate Arrays (FPGA), Application Specific Integrated Circuits (ASIC), Application Specific Standard Products (ASSP), System on Chip (SOC), Complex Programmable Logic Devices (CPLD), and the like.
[0112] In the context of the present disclosure, a machine-readable medium may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0113] The above description is only a preferred embodiment of the present disclosure and an illustration of the applied technical principles. Those skilled in the art should understand that the scope of the disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the (but not limited to) technical features having similar functions disclosed in the present disclosure.
[0114] In addition, although the operations are depicted in a particular order, this should not be construed as requiring that the operations be performed in the particular order shown or in sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments may also be implemented combinatorially in a single embodiment. Conversely, the various features described in the context of a single embodiment may also be implemented separately or in any suitable sub-combination in multiple embodiments.
[0115] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. On the contrary, the specific features and acts described above are merely example forms for implementing the claims.
Claims
1. An image processing method, characterized in that, Comprising: Obtain an original image and adjustment parameters, wherein the adjustment parameters have a mapping relationship with candidate adjustment curves in a candidate adjustment curve set, the candidate adjustment curves include a base curve and a correction curve, and the correction curve is used to correct the pixel output value of the base curve; Obtain a target adjustment curve in the candidate adjustment curve set according to the adjustment parameters; Determine a target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determine a target image according to the target pixel value, wherein the target pixel value represents the corrected pixel output value.
2. The method according to claim 1, characterized in that, The correction curve represents a curve with a positive pixel output value passing through a target coordinate point and within a target interval, and the target interval represents a numerical interval determined based on the abscissa of the target coordinate point.
3. The method according to claim 1, characterized in that, The correction method of the correction curve includes: For the original pixel value in the original image, determine the pixel correction value corresponding to the original pixel value on the correction curve; Based on the pixel correction value, correct the pixel output value output by the base curve based on the original pixel value, so as to correct the deviation between the pixel output value of the base curve and the original pixel value.
4. The method according to claim 1, characterized in that, The candidate adjustment curve set includes a dark part adjustment curve group and a bright part adjustment curve group, and the bright part adjustment curve group is obtained by rotating a set angle with a set coordinate point as the rotation center based on the dark part adjustment curve in the dark part adjustment curve group.
5. The method according to claim 4, wherein The obtaining the target adjustment curve in the candidate adjustment curve set according to the adjustment parameters includes: If the adjustment parameter is a dark part adjustment parameter, determine a dark part curve coefficient corresponding to the dark part adjustment parameter, and obtain a target dark part adjustment curve in the dark part adjustment curve group according to the dark part curve coefficient; Or, If the adjustment parameter is a bright part adjustment parameter, determine a bright part curve coefficient corresponding to the bright part adjustment parameter, and obtain a target bright part adjustment curve in the bright part adjustment curve group according to the bright part curve coefficient.
6. The method according to claim 1, wherein The determining the target pixel value based on the original pixel value of the original image according to the target adjustment curve and determining the target image according to the target pixel value includes: For the original pixel value of the original image, obtain the pixel output value determined by the base curve based on the original pixel value, and obtain the pixel correction value determined by the correction curve based on the original pixel value; Superimpose the pixel output value and the pixel correction value to obtain a target pixel value, and use the target pixel value to update the original pixel value of the original image to obtain the target image.
7. The method according to claim 1, wherein Obtaining the adjustment parameters includes: Display a candidate control set in an interaction interface, the candidate control set includes candidate adjustment controls, wherein the candidate adjustment controls include a dark part adjustment control and a bright part adjustment control; Obtain an adjustment event for a target control in the candidate adjustment controls, the adjustment event includes identification information and status information of the target control, and determine the adjustment parameters according to the identification information and the status information.
8. An image processing apparatus, characterized in that, Comprising: A parameter acquisition module for acquiring an original image and adjustment parameters, wherein the adjustment parameters have a mapping relationship with candidate adjustment curves in a candidate adjustment curve set, the candidate adjustment curves include a basic curve and a correction curve, and the correction curve is used to correct the pixel output value of the basic curve; A curve acquisition module for acquiring a target adjustment curve in the candidate adjustment curve set according to the adjustment parameters; An image determination module for determining a target pixel value based on the original pixel value of the original image according to the target adjustment curve, and determining a target image according to the target pixel value, wherein the target pixel value represents the corrected pixel output value.
9. An electronic device, characterized in that, The electronic device includes: One or more processors; A storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the image processing method according to any one of claims 1-7.
10. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions are used to execute the image processing method according to any one of claims 1-7 when executed by a computer processor.