Image quality adjustment method, device, computer equipment and computer readable storage medium

Abstract

The present application discloses a method, device, computer equipment and computer-readable storage medium for adjusting image quality, the method comprising: obtaining brightness distribution information corresponding to a video frame in target video data and a timestamp corresponding to the video frame; determining a target image quality parameter of the video frame based on the brightness distribution information; and adjusting the image quality parameter of the target video data based on the target image quality parameter and the timestamp. The method of the present application can improve the smoothness of video playback and the image quality display effect of video data.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to a method, device, computer equipment and computer-readable storage medium for adjusting image quality. Background Art

[0002] With the rapid development of display technology, consumers have higher and higher requirements for the image quality of display devices. In order to improve the image quality display effect of video data, it is necessary to adjust the image quality parameters of video data. However, the existing image quality adjustment methods have a large amount of calculation, which will affect the smoothness of video data playback when deployed on display devices with limited computing power. Summary of the invention

[0003] The embodiments of the present application provide a method, apparatus, computer device and computer-readable storage medium for adjusting image quality, which can reduce the power consumption of a target display device and alleviate the temperature rise problem of the target display device.

[0004] The technical solution adopted by the present invention to solve the problem is as follows:

[0005] In a first aspect, the present application provides a method for adjusting image quality, comprising:

[0006] Obtain brightness distribution information and timestamps corresponding to video frames in target video data;

[0007] Determine target image quality parameters of the video frame based on the brightness distribution information;

[0008] The image quality parameters of the target video data are adjusted based on the target image quality parameters and the timestamp.

[0009] In some embodiments of the present application, based on the brightness distribution information, the target image quality parameters of the video frame are determined, including:

[0010] Based on the brightness distribution information, determining a brightness saturation value;

[0011] Based on the brightness saturation value, the target image quality parameters of the video frame are determined.

[0012] In some embodiments of the present application, the brightness distribution information includes a plurality of first brightness level values ​​and a first pixel ratio value corresponding to each first brightness level value. Based on the brightness distribution information, the brightness saturation value is determined, including:

[0013] Determine a second pixel ratio value corresponding to each first brightness level value based on the first pixel ratio value corresponding to each first brightness level value;

[0014] Based on the second pixel ratio value, a plurality of second brightness level values ​​are determined from the plurality of first brightness level values; the plurality of second brightness level values ​​are brightness level values ​​whose corresponding second pixel ratio values ​​among the plurality of first brightness level values ​​are greater than a first threshold value;

[0015] The minimum value among the plurality of second brightness level values ​​is determined as the brightness saturation value.

[0016] In some embodiments of the present application, based on the first pixel ratio value corresponding to each first brightness level value, determining the second pixel ratio value corresponding to each first brightness level value includes:

[0017] For any first brightness level value among the plurality of first brightness level values, determining a third brightness level value corresponding to the first brightness level value from the plurality of first brightness level values; the third brightness level value is a brightness level value among the plurality of first brightness level values ​​that is smaller than the first brightness level value;

[0018] The first pixel ratio value corresponding to the first brightness level value and the first pixel ratio value corresponding to the third brightness level value are summed to obtain a second pixel ratio value corresponding to the first brightness level value.

[0019] In some embodiments of the present application, the target image quality parameter includes a target backlight value. Based on the brightness saturation value, the target image quality parameter of the video frame is determined, including:

[0020] Analyze and process the brightness saturation value to obtain an analysis characteristic value;

[0021] Analyze and process the analysis characteristic value and the first parameter to obtain a first backlight value;

[0022] The first backlight value and the second parameter are analyzed and processed to obtain a target backlight value.

[0023] In some embodiments of the present application, the analysis characteristic value is obtained by analyzing and processing the brightness saturation value by a first processing model;

[0024] The first processing model is: P=POWER(n, r1), where P represents the analysis characteristic value, n represents the brightness saturation value, r1 represents the third parameter, and POWER(n, r1) represents calculating n to the power of r1;

[0025] The first backlight value is obtained by analyzing and processing the analysis characteristic value and the first parameter through the second processing model;

[0026] The second processing model is: Gain = r 2 / P, Gain represents the first backlight value, r2 represents the first parameter;

[0027] The target backlight value is obtained by analyzing and processing the first backlight value and the second parameter through a third processing model;

[0028] The third processing model is: BL=ROUND(r3*Gain, 0), BL represents the target backlight value, r3 represents the second parameter, and ROUND(r3*Gain, 0) represents retaining the integer part of r3*Gain.

[0029] In some embodiments of the present application, the brightness distribution information is determined based on the following method:

[0030] Obtain the brightness value of each pixel corresponding to the video frame in the target video data;

[0031] Determine the number of first pixels corresponding to each first brightness level value based on the brightness value of each pixel and the brightness range corresponding to each first brightness level value in the plurality of first brightness level values;

[0032] The first number of pixels and the second number of pixels corresponding to each pixel point are divided to obtain brightness distribution information corresponding to the video frame.

[0033] In a third aspect, the present application further provides a computer device, the computer device comprising:

[0034] one or more processors;

[0035] Memory; and

[0036] One or more applications, wherein the one or more applications are stored in a memory and configured to be executed by a processor to implement any one of the image quality adjustment methods in the first aspect.

[0037] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, and the computer program is loaded by a processor to execute the steps in any one of the image quality adjustment methods in the first aspect.

[0038] The beneficial effects of the present invention are as follows: based on the brightness distribution information, the target image quality parameters of the video frame are determined, and the image quality parameters of the target video data are adjusted based on the target image quality parameters and the timestamp. This can not only reduce the amount of calculation for image quality adjustment and improve the smoothness of video data playback, but also calculate and adjust the image quality parameters of the target video data in real time frame by frame, thereby improving the image quality display effect of the target video data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 is a schematic diagram of the process of the image quality adjustment system provided by an embodiment of the present invention;

[0041] Figure 2 is a flowchart of a method for adjusting image quality provided by an embodiment of the present invention;

[0042] Figure 3 is a schematic diagram of a specific embodiment flow chart of determining target image quality parameters provided by an embodiment of the present invention;

[0043] Figure 4 is a principle block diagram of a picture quality adjustment device provided by an embodiment of the present invention;

[0044] Figure 5 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0046] In the description of this application, the terms "first", "second", "third", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, features defined as "first", "second", "third", etc. may explicitly or implicitly include one or more of the features. In the description of this application, "several" means one or more than one, unless otherwise clearly and specifically defined.

[0047] In this application, the word "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described in this application as "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments. The following description is given to enable any technician in the field to implement and use the present application. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present application can be implemented without using these specific details. In other instances, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present application with unnecessary details. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0048] It should be noted that since the method of the embodiment of the present application is executed in a computer device, the processing objects of each computer device exist in the form of data or information. For example, time is actually time information. It can be understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, they are all corresponding data for processing by the computer device. The details will not be repeated here.

[0049] The embodiments of the present application provide a method, apparatus, computer device and computer-readable storage medium for adjusting image quality, which are described in detail below.

[0050] See also Figure 1 , Figure 1 The scene diagram of the image quality adjustment system provided in the embodiment of the present application, the image quality adjustment system may include a server 100 and a display device 200, the server 100 is used to obtain the target video data from the display device 200, and return the brightness distribution information corresponding to the video frame in the target video data to the display device 200 based on the target video data. The display device 200 is mainly used to obtain the brightness distribution information corresponding to the video frame in the target video data and the timestamp corresponding to the video frame; based on the brightness distribution information, determine the target image quality parameters of the video frame; adjust the image quality parameters of the target video data based on the target image quality parameters and timestamp. Since the brightness distribution information corresponding to the video frame is determined by the server 100, the amount of calculation when the display device 200 performs image quality adjustment can be reduced, thereby improving the smoothness of the playback of the target video data. In addition, since the target image quality parameters of the video frame are determined based on the brightness distribution information corresponding to the video frame, the image quality parameters can be calculated and adjusted in real time frame by frame to improve the image quality display effect of the target video data.

[0051] In other embodiments, the server 100 is mainly used to obtain target video data from the display device 200, determine the brightness distribution information corresponding to the video frame in the target video data and the timestamp corresponding to the video frame based on the target video data, determine the target image quality parameters of the video frame based on the brightness distribution information, and transmit the target image quality parameters and timestamp to the display device 200, so that the display device 200 can adjust the image quality parameters of the target video data based on the target image quality parameters and timestamp. In this case, since the brightness distribution information and the target image quality parameters are determined by the server 100, the display device 200 can adjust the image quality parameters after obtaining the target image quality parameters and timestamp from the server 100. When the display device 200 adjusts the image quality, it is not necessary to perform pixel statistics and determine the image quality parameters, which can further reduce the amount of calculation when the display device 200 adjusts the image quality, and improves the smoothness of the playback of the target video data. In addition, since the target image quality parameters of the video frame are determined based on the brightness distribution information corresponding to the video frame, the image quality parameters can be calculated and adjusted in real time by frame to improve the image quality display effect of the target video data.

[0052] In some embodiments, the display device 200 sends the target video data and the first request information to the server 100, and the server 100 determines to return the brightness distribution information corresponding to the video frame or the target image quality parameters of the video frame to the display device 200 based on the first request information. For example, when the first request information is the first information, the server 100 returns the brightness distribution information corresponding to the video frame to the display device 200, and when the first request information is the second information, the server 100 returns the target image quality parameters of the video frame to the display device 200. In this way, the display device 200 can send the first request information to the server 100 based on whether its own computing power is sufficient, so that the server 100 performs different operations based on the first request information.

[0053] In the embodiment of the present application, the server 100 may be an independent server, or a server network or server cluster composed of servers. For example, the server 100 described in the embodiment of the present application includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud server composed of a plurality of servers. The cloud server is composed of a large number of computers or network servers based on cloud computing.

[0054] Furthermore, the display device 200 used in the embodiment of the present application may be a device including both receiving and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing two-way communication on a two-way communication link. Such a device may include: a cellular or other communication device having a single-line display or a multi-line display or a cellular or other communication device without a multi-line display. The display device 200 may specifically be one of a television, a mobile phone, a tablet computer, a laptop computer, and the like.

[0055] It should be noted that Figure 1 The scenario diagram of the picture quality adjustment system shown is merely an example. The picture quality adjustment system and scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can appreciate that with the evolution of the picture quality adjustment system and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is equally applicable to similar technical problems.

[0056] In other embodiments, the image quality adjustment system may further include a memory for storing data, such as brightness information, such as brightness distribution information, brightness saturation value, etc., such as backlight values, such as a first backlight value, a second backlight value, etc.

[0057] First, a picture quality adjustment method is provided in an embodiment of the present application. The executor of the picture quality adjustment method is a picture quality adjustment device, and the picture quality adjustment device is applied to a computer device. The picture quality adjustment method includes: obtaining brightness distribution information corresponding to a video frame in target video data and a timestamp corresponding to the video frame; determining target picture quality parameters of the video frame based on the brightness distribution information; and adjusting the picture quality parameters of the target video data based on the target picture quality parameters and the timestamp.

[0058] like Figure 2 FIG. 2 is a flow chart of an embodiment of a method for adjusting image quality in an embodiment of the present application. The method for adjusting image quality may include the following steps S201 to S203, which are as follows:

[0059] Step S201: Obtain brightness distribution information corresponding to a video frame in target video data and a timestamp corresponding to the video frame.

[0060] In the embodiment of the present application, the target video data is the video data to be played, and the target video data includes multiple video frames. The brightness distribution information is used to characterize the brightness distribution of all pixels in the video frame. The brightness distribution information includes a plurality of first brightness level values ​​and a first pixel ratio value corresponding to each first brightness level value. The first pixel ratio value is the ratio of the number of pixels belonging to the first brightness level value in the video frame to the total number of pixels in the video frame. For example, the brightness distribution information can be expressed as Ln={y0, y1, …, yn-1},y i It represents the ratio of the number of pixels belonging to the i-th brightness level value in the video frame to the total number of pixels in the video frame.

[0061] Furthermore, the timestamp corresponding to the video frame indicates the display time of the video frame in the video stream, which can characterize when the video frame should be displayed after being decoded. Optionally, the brightness distribution information corresponding to the video frame in the target video data and the timestamp corresponding to the video frame can be information obtained from other computer devices through the network, Bluetooth, infrared and other means, and the brightness distribution information corresponding to the video frame in the target video data and the timestamp corresponding to the video frame can also be information directly determined by the computer device. For example, when the image quality adjustment method of the present application is applied to a display device, the display device can obtain the brightness distribution information corresponding to the video frame in the target video data and the timestamp corresponding to the video frame from the cloud server through the network, Bluetooth, infrared and other means; when the image quality adjustment method of the present application is applied to a cloud server, the cloud server can obtain the target video data to be played, and decompose and count the pixels of the target video data, so as to obtain the brightness distribution information corresponding to the video frame in the target video data and the timestamp corresponding to the video frame.

[0062] In some embodiments, the brightness distribution information is determined based on the following method: obtaining the brightness value of each pixel point corresponding to the video frame in the target video data; determining the number of first pixels corresponding to each first brightness level value based on the brightness value of each pixel point and the brightness range corresponding to each first brightness level value in a number of first brightness level values; dividing the first pixel number and the second pixel number corresponding to each pixel point to obtain the brightness distribution information corresponding to the video frame.

[0063] In the embodiment of the present application, the brightness value of each pixel represents the grayscale value of each pixel, which can characterize the brightness of each pixel. The value range of the brightness value is usually [0, 255], where 0 represents black and 255 represents white. For a video frame in an RGB color space, the brightness value is jointly determined by the values ​​of the three channels R, G, and B. For a video frame in a YUV color space, the value of the Y channel is the brightness value.

[0064] Furthermore, several first brightness level values ​​are pre-set brightness level values, and each first brightness level value has a corresponding brightness range. For example, several first brightness level values ​​are 0 to 31, and the brightness ranges corresponding to several first brightness level values ​​are [0, 7], [8, 15], ..., [248, 255], respectively. The first number of pixels corresponding to each first brightness level value refers to the number of pixel points in each pixel point whose pixel values ​​are within the brightness range corresponding to the first brightness level value. For example, if the number of pixel points in the range of [0, 7] is 10, then the number of first pixels corresponding to the first brightness level value 0 is 10.

[0065] In the embodiment of the present application, the second number of pixels refers to the total number of each pixel point, the brightness distribution information includes a plurality of first brightness level values ​​and a first pixel ratio value corresponding to each first brightness level value, and the determination process of the first pixel ratio value corresponding to the i-th brightness level value in the brightness distribution information can be expressed as: Among them, y i Indicates the first pixel ratio corresponding to the i-th brightness level value, N i represents the number of first pixels corresponding to the i-th brightness level value, and S represents the number of second pixels.

[0066] Step S202: Determine target image quality parameters of the video frame based on the brightness distribution information.

[0067] In the embodiment of the present application, the target picture quality parameter is a picture quality parameter, which is a key parameter for measuring the picture quality of the display device. In some embodiments, the target picture quality parameter includes at least one of a one-dimensional color lookup table (1D Lookup Table, 1D LUT), a three-dimensional color lookup table (3D Lookup Table, 3D LUT), a backlight value, a contrast ratio, a color temperature, and an HSV histogram.

[0068] Optionally, this embodiment can determine the target image quality parameters of each frame of the target video data based on the brightness distribution information corresponding to the video frame, or can determine the target image quality parameters for the video frames in the target video data based on the brightness distribution information according to a preset frame interval, which is not limited in this embodiment.

[0069] In some embodiments, the above-mentioned step of determining the target image quality parameters of the video frame based on the brightness distribution information specifically includes: performing scene detection on the video frame to obtain scene detection result information; and determining the target image quality parameters of the video frame based on the scene detection result information and the brightness distribution information.

[0070] In an embodiment of the present application, when determining the target image quality parameters of a video frame based on scene detection result information and brightness distribution information, it can be determined based on the scene detection result information whether the scene of the video frame switches. If no switch occurs, there is no need to determine the target image quality parameters of the video frame. If the scene of the video frame switches, the target image quality parameters of the video frame are determined based on the brightness distribution information. In this way, for multiple video frames of the same scene, it is only necessary to determine the target image quality parameters once, avoiding determining the target image quality parameters for all video frames in the target video data, which can reduce the amount of calculation for image quality adjustment and improve the smoothness of video playback. At the same time, since the video frames of the same scene can be adjusted for image quality based on the target image quality parameters corresponding to the scene, the image quality display effect of the target video data can be guaranteed.

[0071] Step S203: adjusting the image quality parameters of the target video data based on the target image quality parameters and the timestamp.

[0072] In an embodiment of the present application, target image quality parameters of the video frame are determined based on the brightness distribution information corresponding to the video frame, and the image quality parameters of the video frame are adjusted based on the target image quality parameters and the timestamp. This can not only reduce the amount of calculation for image quality adjustment and improve the smoothness of video data playback, but also calculate and adjust the image quality parameters of the target video data in real time frame by frame, thereby improving the image quality display effect of the target video data.

[0073] In some embodiments, when the image quality adjustment method is applied to a server, the above-mentioned step of adjusting the image quality parameters of the target video data based on the target image quality parameters and timestamp includes: sending the target image quality parameters and timestamp to a display device to adjust the image quality parameters of the target video data through the display device.

[0074] In other embodiments, the picture quality adjustment method is applied to a display device, and the display device plays the target video data through a target player. The above-mentioned step of adjusting the picture quality parameters of the target video data based on the target picture quality parameters and timestamp includes: transmitting the target picture quality parameters and timestamp to the target player, so as to adjust the picture quality parameters of the target video data through the target player.

[0075] In some embodiments, reference Figure 3 As shown, in the above step S202, based on the brightness distribution information, determining the target image quality parameters of the video frame may include steps S301 to S302, which are specifically as follows:

[0076] Step S301: Determine a brightness saturation value based on brightness distribution information.

[0077] In the embodiment of the present application, the brightness saturation value refers to the brightness level value when the cumulative pixel ratio reaches the first threshold. For example, the first threshold is 0.98. When the brightness level value is 30, the cumulative pixel ratio is greater than 0.98, and the brightness saturation value is 30.

[0078] In some embodiments, the brightness distribution information includes several first brightness level values ​​and a first pixel ratio value corresponding to each first brightness level value. Based on the brightness distribution information, the step of determining the brightness saturation value specifically includes: determining the second pixel ratio value corresponding to each first brightness level value based on the first pixel ratio value corresponding to each first brightness level value; determining several second brightness level values ​​from several first brightness level values ​​based on the second pixel ratio value; and determining the minimum value among the several second brightness level values ​​as the brightness saturation value.

[0079] In the embodiment of the present application, a plurality of second brightness level values ​​are brightness level values ​​whose corresponding second pixel ratio values ​​among a plurality of first brightness level values ​​are greater than a first threshold value. For example, a second pixel ratio value corresponding to a first brightness level value of 29 is 0.85, a second pixel ratio value corresponding to a first brightness level value of 30 is 0.985, and a second pixel ratio value corresponding to a first brightness level value of 31 is 1. The plurality of second brightness level values ​​include 30 and 31. The brightness saturation value is the minimum value among the plurality of second brightness level values. For example, if the plurality of second brightness level values ​​include 30 and 31, the brightness saturation value is 30.

[0080] In some embodiments, the second pixel proportion value is the cumulative pixel proportion value corresponding to each first brightness level value, and based on the first pixel proportion value corresponding to each first brightness level value, the step of determining the second pixel proportion value corresponding to each first brightness level value specifically includes: for any first brightness level value among several first brightness level values, determining the third brightness level value corresponding to the first brightness level value from several first brightness level values; summing the first pixel proportion value corresponding to the first brightness level value and the first pixel proportion value corresponding to the third brightness level value to obtain the second pixel proportion value corresponding to the first brightness level value.

[0081] In an embodiment of the present application, the third brightness level value is a brightness level value among several first brightness level values ​​that is smaller than the first brightness level value. For example, the several first brightness level values ​​include 0, 1, 2, ..., 31. For the first brightness level value 10 among the several first brightness level values, the third brightness level value corresponding to the first brightness level value 10 includes 0, 1, 2, ..., 9.

[0082] S302: Determine a target image quality parameter of the video frame based on the brightness saturation value.

[0083] In the embodiments of the present application, the target picture quality parameters include at least one of a one-dimensional color lookup table (1D Lookup Table, 1DLUT), a three-dimensional color lookup table (3D Lookup Table, 3D LUT), a backlight value, a contrast ratio, a color temperature, and an HSV histogram. Based on the brightness saturation value, the embodiments determine the target picture quality parameters of the video frame, which can improve the accuracy of the determined target picture quality parameters.

[0084] In some embodiments, the target picture quality parameter includes a target backlight value. The steps of determining the target picture quality parameter of the video frame based on the brightness saturation value specifically include: analyzing and processing the brightness saturation value to obtain an analysis eigenvalue; analyzing and processing the analysis eigenvalue and a first parameter to obtain a first backlight value; and analyzing and processing the first backlight value and a second parameter to obtain the target backlight value.

[0085] In some embodiments, the analysis eigenvalue is obtained by analyzing and processing the brightness saturation value through a first processing model, where the first processing model is: P = POWER(n, r1), where P represents the analysis eigenvalue, n represents the brightness saturation value, r1 represents a third parameter, and POWER(n, r1) represents calculating the r1-th power of n.

[0086] Optionally, the third parameter can be set according to actual requirements. In a specific embodiment, 1 ≤ r1 ≤ 3. Optionally, r1 = 2.2, then the first processing model is: P = POWER(n, 2.2), that is, the analysis eigenvalue is obtained by calculating the 2.2-th power of n.

[0087] In some embodiments, the first backlight value is obtained by analyzing and processing the analysis eigenvalue and a first parameter through a second processing model, where the second processing model is: Gain = r 2 / P, where Gain represents the first backlight value and r2 represents the first parameter.

[0088] Optionally, the first parameter can be set according to actual requirements. In a specific embodiment, 0 < r2 ≤ 1. Optionally, r2 = 1, then the second processing model is: Gain = 1 / P, that is, the first backlight value is obtained by dividing the first parameter by the analysis eigenvalue.

[0089] In some embodiments, the target backlight value is obtained by analyzing and processing the first backlight value and the second parameter through a third processing model, where the third processing model is: BL = ROUND(r3 * Gain, 0), BL represents the target backlight value, r3 represents the second parameter, and ROUND(r3 * Gain, 0) represents keeping the integer part of r3 * Gain. That is to say, the process of determining the target backlight value is: multiplying the first backlight value and the second parameter to obtain a second backlight value; performing rounding processing on the second backlight value to obtain the target backlight value.

[0090] Optionally, the second parameter can be set according to actual requirements. In some embodiments, 90 < r3 ≤ 100. Optionally, r3 = 100, then the third processing model is: BL = ROUND(100 * Gain, 0).

[0091] To better implement the image quality adjustment method in the embodiments of the present application, based on the image quality adjustment method, an image quality adjustment device is further provided in the embodiments of the present application, as Figure 4 shown. The image quality adjustment device 600 includes:

[0092] An information acquisition module 610, configured to acquire the brightness distribution information corresponding to the video frame in the target video data and the time stamp corresponding to the video frame;

[0093] A parameter determination module 620, configured to determine the target image quality parameter of the video frame based on the brightness distribution information;

[0094] An image quality adjustment module 630, configured to adjust and process the image quality parameter of the target video data based on the target image quality parameter and the time stamp.

[0095] In the embodiments of the present application, determining the target image quality parameter of the video frame based on the brightness distribution information and adjusting and processing the image quality parameter of the target video data based on the target image quality parameter and the time stamp can not only reduce the calculation amount of image quality adjustment and improve the smoothness of video data playback, but also calculate and adjust the image quality parameter frame by frame for the target video data to improve the image quality display effect of the target video data.

[0096] In some embodiments of the present application, the parameter determination module 620 determines the target image quality parameter of the video frame based on the brightness distribution information, including:

[0097] Determining the brightness saturation value based on the brightness distribution information;

[0098] Determining the target image quality parameter of the video frame based on the brightness saturation value.

[0099] In some embodiments of the present application, the brightness distribution information includes a plurality of first brightness level values ​​and a first pixel ratio value corresponding to each first brightness level value. The parameter determination module 620 determines the brightness saturation value based on the brightness distribution information, including:

[0100] Determine a second pixel ratio value corresponding to each first brightness level value based on the first pixel ratio value corresponding to each first brightness level value;

[0101] Based on the second pixel ratio value, a plurality of second brightness level values ​​are determined from the plurality of first brightness level values; the plurality of second brightness level values ​​are brightness level values ​​whose corresponding second pixel ratio values ​​among the plurality of first brightness level values ​​are greater than a first threshold value;

[0102] The minimum value among the plurality of second brightness level values ​​is determined as the brightness saturation value.

[0103] In some embodiments of the present application, the parameter determination module 620 determines the second pixel ratio value corresponding to each first brightness level value based on the first pixel ratio value corresponding to each first brightness level value, including:

[0104] For any first brightness level value among the plurality of first brightness level values, determining a third brightness level value corresponding to the first brightness level value from the plurality of first brightness level values; the third brightness level value is a brightness level value among the plurality of first brightness level values ​​that is smaller than the first brightness level value;

[0105] The first pixel ratio value corresponding to the first brightness level value and the first pixel ratio value corresponding to the third brightness level value are summed to obtain a second pixel ratio value corresponding to the first brightness level value.

[0106] In some embodiments of the present application, the target image quality parameter includes a target backlight value. The parameter determination module 620 determines the target image quality parameter of the video frame based on the brightness saturation value, including:

[0107] Analyze and process the brightness saturation value to obtain an analysis characteristic value;

[0108] Analyze and process the analysis characteristic value and the first parameter to obtain a first backlight value;

[0109] The first backlight value and the second parameter are analyzed and processed to obtain a target backlight value.

[0110] In some embodiments of the present application, the analysis characteristic value is obtained by analyzing and processing the brightness saturation value by a first processing model;

[0111] The first processing model is: P=POWER(n, r1), where P represents the analysis characteristic value, n represents the brightness saturation value, r1 represents the third parameter, and POWER(n, r1) represents calculating n to the power of r1;

[0112] The first backlight value is obtained by analyzing and processing the analysis characteristic value and the first parameter through the second processing model;

[0113] The second processing model is: Gain = r 2 / P, Gain represents the first backlight value, r2 represents the first parameter;

[0114] The target backlight value is obtained by analyzing and processing the first backlight value and the second parameter through a third processing model;

[0115] The third processing model is: BL=ROUND(r3*Gain, 0), BL represents the target backlight value, r3 represents the second parameter, and ROUND(r3*Gain, 0) represents retaining the integer part of r3*Gain.

[0116] In some embodiments of the present application, the brightness distribution information is determined by the information acquisition module 610 based on the following method:

[0117] Obtain the brightness value of each pixel corresponding to the video frame in the target video data;

[0118] Determine the number of first pixels corresponding to each first brightness level value based on the brightness value of each pixel point and the brightness range corresponding to each first brightness level value in the plurality of first brightness level values;

[0119] The first number of pixels and the second number of pixels corresponding to each pixel point are divided to obtain brightness distribution information corresponding to the video frame.

[0120] The embodiment of the present application further provides a computer device, which integrates any one of the image quality adjustment devices provided in the embodiment of the present application, and the computer device includes:

[0121] one or more processors;

[0122] Memory; and

[0123] One or more applications, wherein the one or more applications are stored in a memory and are configured to execute, by a processor, the steps of the image quality adjustment method in any of the above-mentioned image quality adjustment method embodiments.

[0124] The present application also provides a computer device that integrates any of the image quality adjustment devices provided in the present application. Figure 5As shown, it shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:

[0125] The computer device may include one or more processing core processors 801, one or more computer-readable storage media memories 802, a power supply 803, an input unit 804 and other components. Those skilled in the art will appreciate that Figure 5 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:

[0126] The processor 801 is the control center of the computer device. It uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and / or modules stored in the memory 802 and calling data stored in the memory 802, it executes various functions of the computer device and processes data, thereby monitoring the computer device as a whole. Optionally, the processor 801 may include one or more processing cores; preferably, the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 801.

[0127] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 802 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.

[0128] The computer device also includes a power supply 803 for supplying power to each component. Preferably, the power supply 803 can be logically connected to the processor 801 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 803 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0129] The computer device may further include an input unit 804, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0130] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 801 in the computer device will load the executable files corresponding to the processes of one or more application programs into the memory 802 according to the following instructions, and the processor 801 will run the application programs stored in the memory 802, thereby realizing various functions, as follows:

[0131] Obtain brightness distribution information and timestamps corresponding to video frames in target video data;

[0132] Determine target image quality parameters of the video frame based on the brightness distribution information;

[0133] The image quality parameters of the target video data are adjusted based on the target image quality parameters and the timestamp.

[0134] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0135] To this end, an embodiment of the present application provides a computer-readable storage medium, which may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any one of the image quality adjustment methods provided in the embodiments of the present application. For example, the computer program loaded by the processor can execute the following steps:

[0136] Obtain brightness distribution information and timestamps corresponding to video frames in target video data;

[0137] Determine target image quality parameters of the video frame based on the brightness distribution information;

[0138] The image quality parameters of the target video data are adjusted based on the target image quality parameters and the timestamp.

[0139] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the detailed description of other embodiments above, and will not be repeated here.

[0140] In specific implementation, the above units or structures can be implemented as independent entities, or can be arbitrarily combined to be implemented as the same or several entities. The specific implementation of the above units or structures can refer to the previous method embodiments, which will not be repeated here.

[0141] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0142] The above is a detailed introduction to a method, device, computer equipment and computer-readable storage medium for adjusting image quality provided in an embodiment of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for adjusting image quality, characterized in that: include: Obtaining brightness distribution information corresponding to a video frame in target video data and a timestamp corresponding to the video frame; Based on the brightness distribution information, determining a target image quality parameter of the video frame; The image quality parameters of the target video data are adjusted based on the target image quality parameters and the timestamp.

2. The image quality adjustment method according to claim 1, characterized in that: The determining the target image quality parameter of the video frame based on the brightness distribution information includes: Based on the brightness distribution information, determining a brightness saturation value; Based on the brightness saturation value, a target image quality parameter of the video frame is determined.

3. The image quality adjustment method according to claim 2, characterized in that: The brightness distribution information includes a plurality of first brightness level values ​​and a first pixel ratio value corresponding to each of the first brightness level values; The step of determining a brightness saturation value based on the brightness distribution information includes: Determine a second pixel ratio value corresponding to each first brightness level value based on a first pixel ratio value corresponding to each first brightness level value; Based on the second pixel ratio value, determining a plurality of second brightness level values ​​from a plurality of first brightness level values; a plurality of second brightness level values ​​are brightness level values ​​whose corresponding second pixel ratio values ​​among a plurality of first brightness level values ​​are greater than a first threshold; The minimum value among a plurality of the second brightness level values ​​is determined as the brightness saturation value.

4. The image quality adjustment method according to claim 3, characterized in that: The determining, based on the first pixel proportion value corresponding to each first brightness level value, the second pixel proportion value corresponding to each first brightness level value comprises: For any of the first brightness level values ​​among the plurality of first brightness level values, determine a third brightness level value corresponding to the first brightness level value from the plurality of first brightness level values; the third brightness level value is a brightness level value among the plurality of first brightness level values ​​that is smaller than the first brightness level value; The first pixel ratio value corresponding to the first brightness level value and the first pixel ratio value corresponding to the third brightness level value are summed to obtain a second pixel ratio value corresponding to the first brightness level value.

5. The image quality adjustment method according to claim 2, characterized in that: The target image quality parameters include a target backlight value; The determining, based on the brightness saturation value, a target image quality parameter of the video frame includes: Analyzing and processing the brightness saturation value to obtain an analysis characteristic value; Analyzing and processing the analysis characteristic value and the first parameter to obtain a first backlight value; The first backlight value and the second parameter are analyzed and processed to obtain a target backlight value.

6. The image quality adjustment method according to claim 5, characterized in that: The analysis characteristic value is obtained by analyzing and processing the brightness saturation value through a first processing model; Wherein, the first processing model is: P=POWER(n, r1), wherein P represents the analysis characteristic value, n represents the brightness saturation value, r1 represents the third parameter, and POWER(n, r1) represents calculating n to the power of r1; The first backlight value is obtained by analyzing and processing the analysis characteristic value and the first parameter through a second processing model; Wherein, the second processing model is: Gain = r 2 / P, Gain represents the first backlight value, r2 represents the first parameter; The target backlight value is obtained by analyzing and processing the first backlight value and the second parameter through a third processing model; The third processing model is: BL=ROUND(r3*Gain, 0), BL represents the target backlight value, r3 represents the second parameter, and ROUND(r3*Gain, 0) represents retaining the integer part of r3*Gain.

7. The image quality adjustment method according to any one of claims 1 to 6, characterized in that: The brightness distribution information is determined based on the following method: Obtain the brightness value of each pixel corresponding to the video frame in the target video data; Determine the number of first pixels corresponding to each of the first brightness level values ​​based on the brightness value of each of the pixel points and the brightness range corresponding to each of the first brightness level values ​​among the plurality of first brightness level values; The first number of pixels and the second number of pixels corresponding to each of the pixel points are divided to obtain brightness distribution information corresponding to the video frame.

8. A device for adjusting image quality, characterized in that: include: An information acquisition module, used to acquire brightness distribution information corresponding to a video frame in target video data and a timestamp corresponding to the video frame; A parameter determination module, used to determine a target image quality parameter of the video frame based on the brightness distribution information; The image quality adjustment module is used to adjust the image quality parameters of the target video data based on the target image quality parameters and the timestamp.

9. A computer device, characterized in that: The computer device comprises: one or more processors; Memory; and One or more application programs, wherein the one or more application programs are stored in the memory and are configured to be executed by the processor to implement the image quality adjustment method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the image quality adjustment method according to any one of claims 1 to 7.

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