WO2021098518A1

WO2021098518A1 - Image adjustment method and apparatus, electronic device, and storage medium

Info

Publication number: WO2021098518A1
Application number: PCT/CN2020/126581
Authority: WO
Inventors: 姚坤
Original assignee: RealMe重庆移动通信有限公司
Priority date: 2019-11-18
Filing date: 2020-11-04
Publication date: 2021-05-27
Also published as: CN110855958A; CN110855958B

Abstract

An image adjustment method and apparatus, an electronic device, and a storage medium, relating to the technical field of image processing. The method comprises: obtaining an image to be processed, and determining attribute information of said image, the attribute information comprising any one or a combination of scene information, saturation, and brightness information; determining, according to the attribute information, that a detection result of said image meets an adjustment condition, and determining a color to be adjusted from colors corresponding to a plurality of color channels of said image; and adjusting said color to obtain a target image. Color adjustment can be locally carried out, and the color adjustment accuracy is improved.

Description

Image adjustment method and device, electronic equipment, and storage medium

This application claims the priority of the Chinese patent application filed on November 18, 2019, the application number is 201911128015.5, and the title is "Image adjustment method and device, electronic equipment, storage medium", the entire content of which is incorporated into this application by reference in.

Technical field

The present disclosure relates to the technical field of image processing, and in particular, to an image adjustment method, an image adjustment device, electronic equipment, and a computer-readable storage medium.

Background technique

In the process of capturing images through a camera, how to improve image quality is the key to improving user experience.

In the related art, the initial shooting parameters of the pure color image are adjusted mainly according to the number of color components corresponding to each color channel in the collected image. Or by detecting the scene, and then using the effect parameters suitable for the scene to optimize the image quality.

In the above method, only the pure color image can be adjusted, or the overall image can be improved, and the operation has certain limitations, resulting in poor image quality.

Summary of the invention

The purpose of the present disclosure is to provide an image adjustment method and device, electronic equipment, and storage medium, so as to overcome at least to a certain extent the problem of limitations in color adjustment due to limitations and defects of related technologies.

Other characteristics and advantages of the present disclosure will become apparent through the following detailed description, or partly learned through the practice of the present disclosure.

According to one aspect of the present disclosure, there is provided an image adjustment method, including: acquiring a to-be-processed image and determining multiple attribute information of the to-be-processed image, the attribute information including any of scene information, saturation, and brightness information One or a combination thereof; determining, according to the attribute information, that the detection result for the image to be processed satisfies the adjustment condition, and determining the color to be adjusted from the colors corresponding to the multiple color channels of the image to be processed; The color is adjusted to obtain the target image.

According to one aspect of the present disclosure, there is provided an image adjustment device, including: an attribute information acquisition module for acquiring an image to be processed and determining attribute information of the image to be processed, the attribute information including scene information, saturation, and Any one or a combination of brightness information; the color to-be-adjusted determining module is configured to determine, according to the attribute information, that the detection result of the image to be processed satisfies the adjustment condition, then from the multiple color channels of the image to be processed The color to be adjusted is determined from the corresponding colors; the color adjustment module is used to perform an adjustment operation on the color to be adjusted to obtain a target image.

According to one aspect of the present disclosure, there is provided an electronic device including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute by executing the executable instructions The image adjustment method described in any one of the above.

According to one aspect of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the image adjustment method described in any one of the above is implemented.

It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure.

Description of the drawings

The drawings herein are incorporated into the specification and constitute a part of the specification, show embodiments in accordance with the disclosure, and together with the specification are used to explain the principle of the disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

Fig. 1 schematically shows a system architecture diagram for implementing an image adjustment method in an embodiment of the present disclosure.

Fig. 2 schematically shows a schematic diagram of an image adjustment method in an embodiment of the present disclosure.

FIG. 3 schematically shows a schematic diagram of the overall flow of determining a detection result in an embodiment of the present disclosure.

Fig. 4 schematically shows a flow chart of adjusting saturation in an embodiment of the present disclosure.

Fig. 5 schematically shows a block diagram of an image adjustment device in an embodiment of the present disclosure.

Fig. 6 schematically shows a block diagram of an electronic device in an embodiment of the present disclosure.

Detailed ways

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms, and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed To those skilled in the art. The described features, structures or characteristics can be combined in one or more embodiments in any suitable way. In the following description, many specific details are provided to give a sufficient understanding of the embodiments of the present disclosure. However, those skilled in the art will realize that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, the well-known technical solutions are not shown or described in detail to avoid overwhelming the crowd and obscure all aspects of the present disclosure.

In addition, the drawings are only schematic illustrations of the present disclosure, and are not necessarily drawn to scale. The same reference numerals in the figures denote the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in the form of software, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and/or processor devices and/or microcontroller devices.

In the embodiment of the present disclosure, a system structure diagram for implementing image adjustment is first provided. As shown in FIG. 1, the system architecture 100 may include a first end 101, a network 102, and a second end 103. Among them, the first terminal 101 may be a client, for example, various handheld devices (smart phones) with camera functions, desktop computers, vehicle-mounted devices, wearable devices, and so on. The network 102 is a medium used to provide a communication link between the first end 101 and the second end 103. The network 102 may include various connection types, such as wired communication links, wireless communication links, and so on. In the embodiments of the present disclosure, Here, the network 102 between the first end 101 and the second end 103 may be a wired communication link, for example, a communication link may be provided through a serial port cable, or may be a wireless communication link, and a communication link may be provided through a wireless network. The second end 103 may be a client terminal, such as a portable computer, a desktop computer, a smart phone, or a terminal device with a photographing function and an image processing function, for adjusting and processing the image. Wherein, when the first end and the second end are both clients, they may be the same client.

It should be understood that the numbers of the first end, the network, and the second end in FIG. 1 are only illustrative. There can be any number of clients, networks, and servers according to implementation needs.

It should be noted that the image adjustment method provided by the embodiments of the present disclosure can be completely executed by the second end or the first end, or partly executed by the first end and partly executed by the second end. The executive body does not make special restrictions. Correspondingly, the image adjustment device can be arranged in the second end 103 or in the first end 101.

In the image adjustment method, image adjustment device, electronic device, and computer-readable storage medium provided in the embodiments of the present disclosure, the detection result is obtained according to the attribute information of the image to be processed, and when the detection result satisfies the adjustment condition, the image The color to be adjusted is determined from the colors corresponding to the multiple color channels, and then the color adjustment operation is performed. On the one hand, since the color to be adjusted can be determined from the colors corresponding to multiple color channels when the detection result meets the adjustment condition, and the color to be adjusted can be one or more of the multiple color channels, thus avoiding the related art The problem that all the color channels of the image can only be adjusted as a whole. Since it is possible to adjust only the color channels that meet the adjustment conditions, the function of locally adjusting the color of a certain color channel is realized, and the accuracy of color adjustment is improved. It can also determine the appropriate adjustment range, thereby improving the image quality. On the other hand, because the detection result can be obtained according to the attribute information, and the color can be adjusted when the detection result meets the adjustment conditions, it avoids the limitations of the related technology that can only adjust the pure color image and can only be adjusted as a whole, and increases the adjustment operation. The conditions of use avoid blind adjustment operations, make the adjustment operations more flexible, more in line with the actual situation, and increase the scope of application.

On the basis of the foregoing system architecture, an image adjustment method is provided in the embodiments of the present disclosure, which can be applied to any application scenario where a camera is used to collect images. Referring to FIG. 2, the image adjustment method may include the following steps:

In step S210, a to-be-processed image is acquired, and multiple attribute information of the to-be-processed image is determined. The attribute information includes any one or a combination of scene information, saturation, and brightness information.

In some embodiments, the image to be processed may be an image captured by a camera, or an image in a shooting state. The image in the shooting state refers to the state in which the preview image is obtained by entering the preview interface, but the image has not yet been generated. The image in the shooting state may be an image shot in any mode of the camera in the terminal device, such as portrait mode, professional mode, vivid mode, etc., which are not limited here. In this case, the image to be processed can be an image captured by various camera modules, which can include, but are not limited to, any of a high-resolution camera, a low-resolution camera (such as a macro camera), and a wide-angle camera. One or more. The format of the image to be processed can be RAW (RAW Image Format). RAW is an unprocessed and uncompressed format. RAW can be conceptualized as original image encoding data. The format of the image to be processed can also be YUV format. Y in YUV represents brightness, which is gray value; while UV represents chromaticity, which is used to describe the color and saturation of the image, and is used to specify the color of the pixel. In the embodiments of the present disclosure, the format of the image to be processed is not limited.

The attribute information of the image to be processed is used to describe the image characteristics of the image to be processed, and the attribute information may include scene information and image information. The scene information refers to the information of the scene environment used to shoot the image to be processed, which can be specifically a background type and a preset scene, and the background type can be a solid-color type or a multi-color type. The preset scene can be, for example, a scene such as the sky or green plants. Image information refers to the information contained in the image itself, such as saturation and brightness information. Saturation can be defined as chroma divided by lightness, which, like chroma, represents the degree of color deviation from gray with the same brightness. Saturation refers to the vividness of the color, also known as the purity of the color. Saturation depends on the ratio of the color component and the decolorizing component (gray) in the color. The larger the color component, the greater the saturation; the larger the achromatic component, the smaller the saturation. The brightness information refers to the brightness of the image. If the gray value is between [0, 255], the larger the gray value, the higher the brightness.

Next, in step S220, it is determined according to the attribute information that the detection result for the image to be processed satisfies the adjustment condition, and the color to be adjusted is determined from the colors corresponding to the multiple color channels of the image to be processed.

In some embodiments, after obtaining the attribute information of the image to be processed, the attribute information can be judged, so as to obtain the final detection result used to measure the image to be processed according to the judgment result of the attribute information. In order to improve accuracy, any one or more of the attribute information can be jointly processed here to evaluate the image to be processed from multiple dimensions and multiple angles, instead of evaluating only according to a certain dimension, adding evaluation The comprehensiveness and accuracy of the image to be processed. After determining the detection result for the image to be processed, it can continue to determine whether the detection result meets the adjustment condition. The adjustment conditions here are used to restrict the color adjustment operation, that is, the restriction on whether to perform the adjustment operation, thereby avoiding the operation of adjusting the color at any time, avoiding the blindness of adjusting the color, and making the color adjustment operation more targeted Sex.

Since each of the attribute information is independent of each other, the filter conditions used to measure each attribute information are also different. Based on this, the attribute information can be judged to obtain multiple judgment results through the filtering conditions of each information in the attribute information; the multiple judgment results are further combined to obtain the detection result for the image to be processed, and it is determined whether the detection result meets the adjustment condition.

Fig. 3 schematically shows a schematic diagram of a flow chart for determining the detection result, referring to Fig. 2, which mainly includes the following steps:

In step S310, the background type of the image to be processed is judged to obtain a first judgment result, and it is determined whether the first judgment result is a multi-color type; if yes, go to step S320; if not, go to step S350 .

In step S320, if the first judgment result is a multi-color type, when it is detected that the first judgment result conforms to a preset scene, the saturation of the colors corresponding to the multiple color channels of the image to be processed is determined. Make a judgment to obtain a second judgment result representing the saturation of each color channel, and determine whether the second judgment result is an unsaturated type; if yes, go to step S330; if no, go to Step S360.

In step S330, if the second judgment result is not saturated, compare the brightness threshold with the brightness information of the image to be processed to obtain a third judgment result representing the brightness information, and determine whether the third judgment result is The brightness information is greater than the brightness threshold; if yes, go to step S340; if not, go to step S370.

In step S340, the detection result is determined according to the first judgment result, the second judgment result, and the third judgment result, and the third judgment result is that the brightness information is greater than the brightness threshold. The detection result satisfies the adjustment condition;

In step S350, if the first judgment result is a pure color type, the first judgment result is used as the detection result, and it is determined that the detection result does not satisfy the adjustment condition;

In step S360, if the second judgment result is oversaturated, the detection result is determined according to the first judgment result and the second judgment result, and it is determined that the detection result does not satisfy the adjustment condition;

In step S370, if the third judgment result is less than the brightness threshold, it is determined that the detection result does not satisfy the adjustment condition.

In the embodiment of the present disclosure, the first judgment result is used to describe whether the background type of the image to be processed is a multi-color type. Specifically, it is possible to detect whether the background used to obtain the image to be processed is of a solid color type by means of artificial intelligence. For example, the type of color used to represent the background image in the scene where the shooting object is located can be recognized. If it contains one color, the background type can be considered as a solid color type; if it contains multiple colors, it can be considered The background type is a multi-color type. After it is determined that the first judgment result is a multi-color type, it can continue to judge whether the first judgment result conforms to the preset scene. The preset scene can be, for example, a multi-color scene such as sky and green plants.

The second judgment result is used to indicate the specific situation of the saturation of the color corresponding to each color channel of the image to be processed, that is, the magnitude relationship between the saturation and the saturation threshold. The color channels can include R channels, G channels, and B channels. Each color channel stores the information of the color elements in the image, and the colors in all the color channels are superimposed and mixed to produce the color of the pixels in the image. Specifically, the current saturation of the color of each color channel can be obtained, and the current saturation can be compared with the saturation threshold of each color channel to obtain whether the current saturation of the color of each color channel is unsaturated or oversaturated The second judgment result. The saturation threshold of each color channel can be the same or different, which is not limited here. It should be noted that when the second judgment result is obtained here, the color saturation of each color channel is evaluated separately, that is, the color saturations of multiple color channels are independent of each other, so the second judgment result It is also for the color of each color channel.

The third judgment result may be used to indicate the magnitude relationship between the brightness information of the color of the entire image to be processed and the preset brightness threshold. Specifically, the brightness information of the image to be processed can be obtained, and the brightness information can be compared with the brightness threshold to obtain the third judgment result that the brightness information is greater than the brightness threshold or less than the brightness threshold.

After obtaining multiple judgment results in different dimensions, the first judgment result, the second judgment result, and the third judgment result can be fused together to obtain the final detection result for screening. When determining the detection result, multiple judgment results are obtained in a sequential order. Specifically, first obtain the first judgment result. If the first judgment result is a multi-color type and the first judgment result matches the preset scene, then continue to obtain the second judgment result; if the first judgment result is a pure color type, there is no need Obtain the second judgment result. Further, if the second judgment result for each color channel is not saturated, continue to obtain the third judgment result and determine the detection result according to the third judgment result; if the second judgment result is oversaturated, there is no need to obtain the third judgment result result. It should be noted that since the second judgment result is made on the basis of the first judgment result, and the third judgment result is made on the basis of the second judgment result, it can be considered that the third judgment result includes the first judgment result. Information about the judgment result and the second judgment result.

Further, the detection result can be determined according to the third judgment result in a sequence. Either the first judgment result is directly determined as the detection result, or the detection result is determined according to the first judgment result and the second judgment result. On the basis of determining the detection result, if the third judgment result is that the brightness information is greater than the brightness threshold, it can be considered that the detection result satisfies the adjustment condition. If the third judgment result is that the brightness information is less than the brightness threshold, it can be considered that the detection result does not satisfy the adjustment condition. If the first judgment result is a pure color type, it can be considered that the detection result does not satisfy the adjustment condition. If the second judgment result is oversaturation, it can be considered that the detection result is that the adjustment condition is not satisfied. It can be seen that, in the technical solution provided in Figure 3, judging whether the detection result of the image to be processed meets the adjustment conditions can be measured in multiple dimensions, thus avoiding limitations, increasing the comprehensiveness of the measurement adjustment operation, and making the adjustment operation more comprehensive. match the true situation.

In some embodiments, when the detection result meets the adjustment condition, the color adjustment operation can be triggered, which can avoid unnecessary operations, reduce operation steps, and avoid misoperation. At the same time, the adjustment operation can be performed when the image to be processed is of a multi-color type conforming to the preset scene, the saturation is not saturated, and the brightness information is greater than the brightness threshold. The adjustment conditions can be triggered by filtering in multiple dimensions, which can improve the adjustment operation Accuracy and pertinence.

When performing adjustment operations, you can first determine the color to be adjusted. The color to be adjusted may be one or more of the colors corresponding to the multiple color channels. Specifically, it may be determined according to the color corresponding to the color channel satisfying the second judgment result when the detection result satisfies the adjustment condition. Specifically, if the detection result satisfies the adjustment condition, the color corresponding to the color channel whose color is not saturated as the second determination result is determined as the color to be adjusted. For example, if the second judgment result of the G channel is not saturated, the G channel can be used as the color to be adjusted; if the second judgment result of the G channel and the B channel are both unsaturated, the G channel and the B channel can be All are used as the color to be adjusted.

In the method in the embodiments of the present disclosure, one or more of the corresponding colors of the R channel, G channel, and B channel can be used as the color to be adjusted. Therefore, a certain color channel can be adjusted separately, which avoids the overall adjustment. The problem of individual color oversaturation can be adjusted locally, avoiding limitations, improving the pertinence and flexibility of color adjustment, increasing the scope of application, and improving image quality.

In step S230, an adjustment operation is performed on the to-be-adjusted color to obtain a target image.

In some embodiments, after determining the color to be adjusted, the color to be adjusted may be adjusted in response to a user operation or automatically to obtain the target image. The target image here refers to the image after the color adjustment of the image to be processed, so there is a difference in color from the image to be processed. The specific steps of adjusting the color to be adjusted may include: determining the degree of adjustment, and adjusting the saturation of the color to be adjusted according to the degree of adjustment. The degree of adjustment refers to the amplitude used to adjust the image, which can be specifically determined according to the difference information between the brightness information of the image to be processed and the brightness threshold. Specifically, under the condition that the brightness information of the image to be processed is greater than the brightness threshold, the difference information between the brightness information and the brightness threshold (that is, the portion where the brightness information is greater than the brightness threshold) can be obtained. The difference information can be negatively correlated with the degree of adjustment, that is, the greater the difference information between the two, the smaller the degree of adjustment; the smaller the difference information between the two, the greater the degree of adjustment. The adjustment degree of each color channel can be determined according to the same rule or different rules. When performing an adjustment operation on the color to be adjusted, the saturation is specifically increased to achieve the purpose of local color enhancement.

The specific steps of color adjustment may include: dividing the image to be processed into blocks to obtain multiple blocks, respectively obtaining the color channel information and attribute information of each block, and then determining the block in each block according to the method in step S220 to step S230. For the color to be adjusted, the saturation of each pixel contained in each block is adjusted one by one, and then all the blocks are merged together to obtain an image after adjusting the saturation.

In the method in the embodiments of the present disclosure, after the detection result of the image to be processed meets the adjustment conditions and the color to be adjusted is determined, the adjustment degree can be determined according to the environmental brightness, and the degree and level of the saturation increase can be determined according to the adjustment degree, so as to avoid blind increase The problem of image saturation and inaccurate adjustment improves the vividness of the image and improves the image quality.

In addition, the method may also include the following two cases: Case 1: If the detection result does not satisfy the adjustment condition, stop performing the adjustment operation. Case 2: If the detection result does not satisfy the adjustment condition, a candidate color is determined from the colors corresponding to the multiple color channels, and a preset adjustment operation is performed on the candidate color. Among them, the candidate color refers to the color of other color channels except the color to be adjusted. When the colors corresponding to the three color channels are all the colors to be adjusted, the candidate color does not exist. The preset adjustment operation may also be an adjustment operation on the saturation of the color, but the adjustment degree of the adjustment operation in step S230 is different. It should be noted that the adjustment degree of the preset adjustment operation may be smaller than the adjustment degree of the adjustment operation, so as to avoid the problems of excessive and inappropriate saturation adjustment and improve the image quality.

Fig. 4 schematically shows a specific flow chart for adjusting saturation, referring to Fig. 4, it mainly includes the following steps:

In step S410, the scene is detected by artificial intelligence.

In step S420, it is determined whether it is a solid-color background image. If yes, go to step S430; if not, go to step S490.

In step S430, it is determined whether it is a preset scene, and the preset scene may be, for example, a multi-color scene such as the sky. If yes, go to step S440.

In step S440, information of multiple color channels of the image to be processed is acquired. The multiple color channels may be R, G, and B channels, and the information of the multiple color channels may be the color saturation of the multiple color channels.

In step S450, it is determined whether the saturation of the multiple color channels is oversaturated. If yes, go to step S490; if not, go to step S460.

In step S460, the brightness information of the image to be processed is acquired.

In step S470, it is determined whether the brightness information is lower than a preset brightness threshold. If yes, go to step S490; if not, go to step S480.

In step S480, the color of the R channel, the G channel, or the B channel is used as the color to be adjusted in combination with the judgment results of the saturation of the multiple color channels, so as to increase the color saturation of the R channel, the G channel or the B channel.

In step S490, no processing is performed or the increase in saturation is weakened.

The technical solution in Figure 4 can be combined with the judgment results of the saturation of multiple color channels, and one or more of the R channel, the G channel, and the B channel can be used as the color to be adjusted, so a certain color channel can be individually adjusted The adjustment avoids the problem of over-saturation of individual colors during overall adjustment, enables partial adjustment, avoids limitations, and improves the pertinence of color adjustment.

In an embodiment of the present disclosure, an image adjustment device is provided. Referring to FIG. 5, the image adjustment device 500 may include:

The attribute information obtaining module 501 is configured to obtain a to-be-processed image and determine multiple attribute information of the to-be-processed image, where the attribute information includes any one or a combination of scene information, saturation, and brightness information;

The to-be-adjusted color determination module 502 is configured to determine, according to the attribute information, that the detection result of the to-be-processed image satisfies the adjustment condition, and determine the to-be-adjusted color from the colors corresponding to the multiple color channels of the to-be-processed image;

The color adjustment module 503 is configured to perform an adjustment operation on the to-be-adjusted color to obtain a target image.

In an exemplary embodiment of the present disclosure, the device further includes: a first acquisition module, configured to detect the scene type of the image to be processed to obtain a first judgment result; and a second acquisition module, configured to determine If the first judgment result is a multi-color type, and if it is detected that the first judgment result conforms to a preset scene, the saturation of the colors corresponding to the multiple color channels of the image to be processed is judged to obtain Used to indicate the second judgment result of the color saturation of each of the color channels; the third acquisition module is used to determine that the second judgment result is that the color is not saturated, and compare the brightness threshold with the brightness information of the image to be processed The comparison is performed to obtain a third judgment result indicating whether the brightness information is greater than the brightness threshold; the detection result judgment module is configured to determine the detection result according to the first judgment result, the second judgment result, and the third judgment result, And when the third judgment result is that the brightness information is greater than the brightness threshold, it is determined that the detection result satisfies the adjustment condition.

In an exemplary embodiment of the present disclosure, the device further includes: determining that the first judgment result is a pure color type, using the first judgment result as the detection result, and determining that the detection result does not satisfy The adjustment condition; or it is determined that the second judgment result is color oversaturation, the detection result is determined according to the first judgment result and the second judgment result, and it is determined that the detection result does not satisfy the adjustment condition; or It is determined that the third judgment result is that the brightness information is less than the brightness threshold, and it is determined that the detection result does not satisfy the adjustment condition.

In an exemplary embodiment of the present disclosure, the to-be-adjusted color determination module is configured to: if the detection result meets the adjustment condition, the second determination result is the color corresponding to the color channel whose color is not saturated Determined to be the color to be adjusted.

In an exemplary embodiment of the present disclosure, the color adjustment module includes: a degree determination module, configured to determine the degree of adjustment, and perform an adjustment operation on the saturation of the color to be adjusted according to the degree of adjustment.

In an exemplary embodiment of the present disclosure, the degree determination module is configured to: if the brightness information is greater than the brightness threshold, determine the adjustment degree according to the difference information between the brightness information and the brightness threshold. , And the adjustment degree is negatively related to the difference information.

In an exemplary embodiment of the present disclosure, the device further includes: a stop adjustment module, configured to stop performing the adjustment operation if the detection result does not satisfy the adjustment condition; or a preset adjustment execution module , For determining a candidate color from the colors corresponding to the multiple color channels if the detection result does not satisfy the adjustment condition, and performing a preset adjustment operation on the candidate color.

It should be noted that the specific details of each module in the above-mentioned image adjustment device have been described in detail in the corresponding image adjustment method, and therefore will not be repeated here.

It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of a module or unit described above can be further divided into multiple modules or units to be embodied.

In addition, although the various steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that these steps must be performed in the specific order, or that all the steps shown must be performed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, etc.

In the embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

Those skilled in the art can understand that various aspects of the present disclosure can be implemented as a system, a method, or a program product. Therefore, various aspects of the present disclosure can be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "Circuit", "Module" or "System".

The electronic device 600 according to this embodiment of the present disclosure will be described below with reference to FIG. 6. The electronic device 600 shown in FIG. 6 is only an example, and should not bring any limitation to the function and scope of use of the embodiments of the present disclosure.

As shown in FIG. 6, the electronic device 600 is represented in the form of a general-purpose computing device. The components of the electronic device 600 may include, but are not limited to: the aforementioned at least one processing unit 610, the aforementioned at least one storage unit 620, a bus 630 connecting different system components (including the storage unit 620 and the processing unit 610), and a display unit 640.

Wherein, the storage unit stores program code, and the program code can be executed by the processing unit 610, so that the processing unit 610 executes various exemplary methods described in the “Exemplary Method” section of this specification. Steps of implementation. For example, the processing unit 610 may perform the steps shown in FIG. 2.

The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 6201 and/or a cache storage unit 6202, and may further include a read-only storage unit (ROM) 6203.

The storage unit 620 may also include a program/utility tool 6204 having a set of (at least one) program module 6205. Such program module 6205 includes but is not limited to: an operating system, one or more application programs, other program modules, and program data, Each of these examples or some combination may include the implementation of a network environment.

The bus 630 may represent one or more of several types of bus structures, including a storage unit bus or a storage unit controller, a peripheral bus, a graphics acceleration interface, a processing unit, or a local area using any bus structure among multiple bus structures. bus.

The electronic device 600 may also communicate with one or more external devices 700 (such as keyboards, pointing devices, Bluetooth devices, etc.), and may also communicate with one or more devices that enable a user to interact with the electronic device 600, and/or communicate with Any device (such as a router, modem, etc.) that enables the electronic device 600 to communicate with one or more other computing devices. This communication can be performed through an input/output (I/O) interface 650. In addition, the electronic device 600 may also communicate with one or more networks (for example, a local area network (LAN), a wide area network (WAN), and/or a public network, such as the Internet) through the network adapter 660. As shown in the figure, the network adapter 660 communicates with other modules of the electronic device 600 through the bus 630. It should be understood that although not shown in the figure, other hardware and/or software modules can be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives And data backup storage system, etc.

In the embodiments of the present disclosure, a computer-readable storage medium is also provided, on which is stored a program product capable of implementing the above-mentioned method in this specification. In some possible implementation manners, various aspects of the present disclosure may also be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to enable the The terminal device executes the steps according to various exemplary embodiments of the present disclosure described in the above-mentioned "Exemplary Method" section of this specification.

The program product for implementing the above method according to the embodiment of the present disclosure may adopt a portable compact disk read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device.

The program product can use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or a combination of any of the above. More specific examples (non-exhaustive list) of readable storage media include: electrical connections with one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable Type programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.

The computer-readable signal medium may include a data signal propagated in baseband or as a part of a carrier wave, and readable program code is carried therein. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. The readable signal medium may also be any readable medium other than a readable storage medium, and the readable medium may send, propagate, or transmit a program for use by or in combination with the instruction execution system, apparatus, or device.

The program code contained on the readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

The program code used to perform the operations of the present disclosure can be written in any combination of one or more programming languages. The programming languages include object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural programming languages. Programming language-such as "C" language or similar programming language. The program code can be executed entirely on the user's computing device, partly on the user's device, executed as an independent software package, partly on the user's computing device and partly executed on the remote computing device, or entirely on the remote computing device or server Executed on. In the case of a remote computing device, the remote computing device can be connected to a user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (for example, using Internet service providers). Business to connect via the Internet).

In addition, the above-mentioned drawings are merely schematic illustrations of the processing included in the method according to the embodiments of the present disclosure, and are not intended for limitation. It is easy to understand that the processing shown in the above drawings does not indicate or limit the time sequence of these processings. In addition, it is easy to understand that these processes can be executed synchronously or asynchronously in multiple modules, for example.

Those skilled in the art will easily think of other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptive changes of the present disclosure. These variations, uses, or adaptive changes follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field that are not disclosed in the present disclosure. . The description and the embodiments are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.

Claims

An image adjustment method, characterized in that it comprises:

Acquiring a to-be-processed image, and determining attribute information of the to-be-processed image, where the attribute information includes any one or a combination of scene information, saturation, and brightness information;

Determining, according to the attribute information, that the detection result of the image to be processed satisfies the adjustment condition, and determining the color to be adjusted from the colors corresponding to the multiple color channels of the image to be processed;

The adjustment operation is performed on the to-be-adjusted color to obtain a target image.
The image adjustment method according to claim 1, wherein the method further comprises:

The attribute information is judged according to the screening conditions of each information in the attribute information, and the detection result is obtained by combining multiple judgment results to determine whether the detection result meets the adjustment condition.
The image adjustment method according to claim 2, characterized in that the attribute information is judged by the filtering conditions of each information in the attribute information, and the detection result is obtained by combining multiple judgment results to determine the Whether the test results meet the adjustment conditions include:

Detecting the background type of the image to be processed to obtain a first judgment result;

If it is determined that the first judgment result is a multi-color type, and if it is detected that the first judgment result matches a preset scene, the saturation of the colors corresponding to the multiple color channels of the image to be processed is judged respectively, to Obtaining a second judgment result used to represent the color saturation of each of the color channels;

It is determined that the second judgment result is that the color is not saturated, and the brightness threshold is compared with the brightness information of the image to be processed to obtain a third judgment result used to indicate whether the brightness information is greater than the brightness threshold;

The detection result is determined according to the first judgment result, the second judgment result, and the third judgment result, and when the third judgment result is that the brightness information is greater than the brightness threshold, it is determined that the detection result satisfies The adjustment conditions.
The image adjustment method according to claim 3, wherein the method further comprises:

Determine that the first judgment result is a pure color type, use the first judgment result as the detection result, and determine that the detection result does not satisfy the adjustment condition; or

Determining that the second judgment result is color oversaturation, determining the detection result according to the first judgment result and the second judgment result, and determining that the detection result does not satisfy the adjustment condition; or

It is determined that the third judgment result is that the brightness information is less than the brightness threshold, and it is determined that the detection result does not satisfy the adjustment condition.
The image adjustment method according to claim 3, wherein determining the color to be adjusted from the colors corresponding to the multiple color channels of the image to be processed comprises:

If the detection result satisfies the adjustment condition, the color corresponding to the color channel whose color is not saturated in the second judgment result is determined as the color to be adjusted.
The image adjustment method according to claim 1, wherein the adjustment operation on the to-be-adjusted color comprises:

The adjustment degree is determined, and the saturation of the to-be-adjusted color is adjusted according to the adjustment degree.
8. The image adjustment method according to claim 6, wherein determining the adjustment degree and adjusting the saturation of the color to be adjusted according to the adjustment degree comprises:

If the brightness information is greater than the brightness threshold, the adjustment degree is determined according to the difference information between the brightness information and the brightness threshold, and the adjustment degree is negatively related to the difference information.
The image adjustment method according to claim 1, wherein the method further comprises:

If the detection result does not satisfy the adjustment condition, stop performing the adjustment operation; or

If the detection result does not satisfy the adjustment condition, a candidate color is determined from the colors corresponding to the multiple color channels, and a preset adjustment operation is performed on the candidate color.
8. The image adjustment method according to claim 8, wherein the adjustment degree of the preset adjustment operation is smaller than the adjustment degree of the adjustment operation.
An image adjustment device, characterized in that it comprises:

The attribute information acquisition module is configured to acquire the image to be processed and determine the attribute information of the image to be processed, the attribute information including any one or a combination of scene information, saturation and brightness information;

A color to-be-adjusted determination module, configured to determine, according to the attribute information, that the detection result for the image to be processed satisfies an adjustment condition, and determine the color to be adjusted from the colors corresponding to the multiple color channels of the image to be processed;

The color adjustment module is used to perform adjustment operations on the to-be-adjusted color to obtain a target image.
The image adjustment device according to claim 10, wherein the device further comprises:

The judgment module is used to judge the attribute information according to the screening conditions of each information in the attribute information, and combine multiple judgment results to obtain the detection result, so as to determine whether the detection result meets the adjustment condition.
The image adjustment device according to claim 11, wherein the judgment module comprises:

The first acquisition module is configured to detect the scene type of the image to be processed to obtain a first judgment result;

The second acquisition module is configured to determine that the first judgment result is of a multi-color type, and if it is detected that the first judgment result matches a preset scene, then the colors corresponding to the multiple color channels of the image to be processed To determine the saturation of each of the color channels to obtain a second determination result representing the color saturation of each of the color channels;

A third acquisition module, configured to determine that the second judgment result is that the color is not saturated, and compare the brightness threshold with the brightness information of the image to be processed to obtain a third judgment result indicating whether the brightness information is greater than the brightness threshold;

The detection result judgment module is configured to determine the detection result according to the first judgment result, the second judgment result, and the third judgment result, and when the third judgment result is that the brightness information is greater than the brightness threshold When it is determined that the detection result meets the adjustment condition.
The image adjustment device according to claim 12, wherein the device further comprises:

A first determination module, configured to use the first determination result as a pure color type, use the first determination result as the detection result, and determine that the detection result does not satisfy the adjustment condition; or

A second determination module, configured to determine that the second determination result is color oversaturation, determine the detection result according to the first determination result and the second determination result, and determine that the detection result does not satisfy the adjustment condition; or

The third determination module is configured to determine that the third determination result is that the brightness information is less than the brightness threshold, and determine that the detection result does not satisfy the adjustment condition.
The image adjustment device according to claim 12, wherein the to-be-adjusted color determination module is configured to: if the detection result satisfies the adjustment condition, the second judgment result is a color channel with an unsaturated color The corresponding color is determined as the color to be adjusted.
The image adjustment device according to claim 10, wherein the color adjustment module comprises:

The degree determination module is used to determine the degree of adjustment, and perform an adjustment operation on the saturation of the color to be adjusted according to the degree of adjustment.
The image adjustment device according to claim 15, wherein the degree determination module is configured to:

If the brightness information is greater than the brightness threshold, the adjustment degree is determined according to the difference information between the brightness information and the brightness threshold, and the adjustment degree is negatively related to the difference information.
The image adjustment device according to claim 10, wherein the device further comprises:

The stop adjustment module is configured to stop performing the adjustment operation if the detection result does not satisfy the adjustment condition; or

The preset adjustment execution module is configured to determine a candidate color from the colors corresponding to the multiple color channels if the detection result does not satisfy the adjustment condition, and perform a preset adjustment operation on the candidate color.
18. The image adjustment device according to claim 17, wherein the adjustment degree of the preset adjustment operation is smaller than the adjustment degree of the adjustment operation.
An electronic device, characterized in that it comprises:

Processor; and

A memory for storing executable instructions of the processor;

Wherein, the processor is configured to execute the image adjustment method according to any one of claims 1-9 by executing the executable instructions.
A computer-readable storage medium with a computer program stored thereon, wherein the computer program implements the image adjustment method according to any one of claims 1-9 when the computer program is executed by a processor.