CN111405345B - Image processing method, image processing device, display device and readable storage medium - Google Patents
Image processing method, image processing device, display device and readable storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/431—Generation of visual interfaces for content selection or interaction; Content or additional data rendering
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/435—Processing of additional data, e.g. decrypting of additional data, reconstructing software from modules extracted from the transport stream
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/47—End-user applications
- H04N21/485—End-user interface for client configuration
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/44—Receiver circuitry for the reception of television signals according to analogue transmission standards
- H04N5/445—Receiver circuitry for the reception of television signals according to analogue transmission standards for displaying additional information
- H04N5/44504—Circuit details of the additional information generator, e.g. details of the character or graphics signal generator, overlay mixing circuits
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Abstract
The embodiment of the application provides an image processing method, an image processing device, a display device and a readable storage medium, wherein a first image to be processed is obtained, and the first image is subjected to image processing to obtain at least one second image; and counting histograms of each second image in at least two dimensions; and identifying whether the first image is an OSD image or not according to the histogram of the second image in each dimension, and further performing enhanced display on the first image by using an enhancement strategy corresponding to the identification result of the first image. In the embodiment of the application, whether the first image is the OSD image or not is determined by using the histograms of at least two dimensions, so that the identification of the OSD image can be effectively realized, and the identification accuracy is high; meanwhile, the first image is enhanced and displayed by utilizing the enhancement strategy corresponding to the identification result of the first image, so that the problem of negative display effect when the first image is an OSD image can be effectively avoided.
Description
Technical Field
The embodiment of the application relates to the technical field of image processing, in particular to an image processing method, an image processing device, display equipment and a readable storage medium.
Background
In order to obtain a better display effect, a mobile device is often equipped with a display enhancement function to improve the contrast, sharpness, brightness, and the like of a picture, and the display enhancement function is generally used for watching videos and browsing scenes of pictures.
At present, images of different scenes have different enhancement strategies, and if the same enhancement strategy is adopted, negative effects occur in part of the scenes, for example, the natural image scene and the text reading scene cannot use the same enhancement strategy, and if the enhancement strategy of the natural image scene is used in the text reading scene, negative effects such as distortion and ghosting can occur.
Based On this, in the prior art, it is necessary to identify a scene of an image and select a corresponding enhancement policy according to the scene in a targeted manner to process the image accordingly, but there is a scene that cannot be identified effectively, that is, an On-Screen Display (OSD) image scene, and if the enhancement policy of a natural image scene is used in the OSD image scene, negative effects such as distortion and ghosting are also easily generated.
Disclosure of Invention
The embodiment of the application provides an image processing method, an image processing device, a display device and a readable storage medium, which can solve the technical problem that in the prior art, a negative display effect is easily generated because an OSD image cannot be effectively identified.
In a first aspect, an embodiment of the present application provides an image processing method, including:
acquiring a first image to be processed;
performing image processing on the first image to obtain at least one second image, and counting histograms of the second image in at least two dimensions;
identifying whether the first image is an OSD image or not according to the histogram of the second image in each dimension;
and performing enhancement display on the first image by using an enhancement strategy corresponding to the identification result of the first image.
In a possible implementation, the identifying whether the first image is an OSD image according to the histogram of the second image in each dimension includes:
acquiring information entropy of the histograms of the second images in all dimensions by utilizing the histograms of the second images in all dimensions;
and identifying whether the first image is an OSD image according to the information entropy of the histogram of the second image in each dimension.
In a possible implementation manner, the identifying whether the first image is an OSD image according to the entropy of the information of the histogram of the second image in each dimension includes:
calculating the product of the information entropies of the histograms of the dimensions of the second image to obtain a confidence parameter of the second image;
obtaining an identification result of the second image according to the confidence parameter of the second image;
and determining whether the first image is an OSD image according to the identification result of the second image.
In a possible implementation manner, the obtaining the recognition result of the second image according to the confidence parameter of the second image includes:
judging whether the confidence parameter of the second image is larger than a preset first threshold value or not;
if the confidence parameter is larger than the first threshold value, determining that the second image is a non-OSD image;
and if the confidence parameter is less than or equal to the first threshold value, determining that the second image is an OSD image.
In a possible implementation manner, before the determining whether the confidence parameter of the second image is greater than the preset first threshold, the method further includes:
judging whether the absolute value of the difference value between the confidence parameter of the second image and the first threshold value is larger than a preset second threshold value or not;
the determining whether the confidence parameter of the second image is greater than a preset first threshold value includes:
if the absolute value is larger than the second threshold, judging whether the confidence parameter of the second image is larger than a preset first threshold.
In one possible embodiment, the method further comprises:
if the absolute value is smaller than or equal to the second threshold, selecting a target dimension from a preset candidate dimension set, and acquiring the information entropy of the histogram of the second image in the target dimension;
calculating the product of the information entropies of the histograms of the second image in all dimensions including the target dimension to obtain a new confidence parameter of the second image;
obtaining a new recognition result of the second image according to the new confidence parameter of the second image;
and determining whether the first image is an OSD image or not according to the new identification result of the second image.
In a possible implementation manner, the determining whether the first image is an OSD image according to the recognition result of the second image includes:
if the number of the second images is one, determining that the identification result of the second images is the identification result of the first images;
if the number of the second images is at least two, determining that the first image is an OSD image when the identification results of all the second images are OSD images; when the identification results of all the second images are non-OSD images, determining that the first image is a non-OSD image; and when the identification result of the partial second image is the OSD image, determining that the first image is the partial OSD image.
In a possible implementation manner, the performing enhanced display on the first image by using an enhancement policy corresponding to the recognition result of the first image includes:
when the first image is a non-OSD image, enhancing and displaying the first image by adopting first image enhancement intensity;
when the first image is a partial OSD image, enhancing and displaying the first image by adopting second image enhancement intensity;
when the first image is an OSD image, enhancing and displaying the first image by adopting a third image enhancement intensity;
wherein the second image enhancement intensity is less than the first image enhancement intensity and greater than the third image enhancement intensity.
In a possible embodiment, the image processing the first image to obtain at least one second image includes:
acquiring display position parameters of a display interface control of display equipment;
cutting the first image by using the display position parameter to obtain a cut first image;
and carrying out region division on the cut first image to obtain at least one second image.
In a second aspect, an embodiment of the present application provides an image processing apparatus, including:
the acquisition module is used for acquiring a first image to be processed;
the processing module is used for carrying out image processing on the first image, acquiring at least one second image and counting histograms of the second image in at least two dimensions;
the identification module is used for identifying whether the first image is an OSD (on screen display) image of the screen display menu according to the histogram of the second image in each dimension;
and the enhancement module is used for enhancing and displaying the first image by utilizing an enhancement strategy corresponding to the identification result of the first image.
In a third aspect, an embodiment of the present application provides a display device, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes computer-executable instructions stored by the memory to cause the at least one processor to perform the image processing method of the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the image processing method according to the first aspect is implemented.
According to the image processing method, the image processing device, the display equipment and the readable storage medium, the first image to be processed is obtained, the first image is subjected to image processing, and at least one second image is obtained; and counting histograms of each second image in at least two dimensions; and identifying whether the first image is an OSD image or not according to the histogram of the second image in each dimension, and further performing enhanced display on the first image by using an enhancement strategy corresponding to the identification result of the first image. In the embodiment of the application, whether the first image is the OSD image or not is determined by using the histograms of at least two dimensions, so that the identification of the OSD image can be effectively realized, and the identification accuracy is high; meanwhile, the first image is enhanced and displayed by utilizing the enhancement strategy corresponding to the identification result of the first image, so that the problem of negative display effect when the first image is an OSD image can be effectively avoided.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a first schematic flowchart of an image processing method provided in an embodiment of the present application;
fig. 2 is a first flowchart illustrating an image processing method provided in an embodiment of the present application;
fig. 3 is a schematic diagram of image processing performed on a first image in an image processing method provided in an embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a refinement step in an image processing method provided in an embodiment of the present application;
fig. 5 is a schematic functional block diagram of an image processing apparatus provided in an embodiment of the present application;
fig. 6 is a schematic diagram of a hardware structure of a display device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application can be applied to various display devices, such as a mobile terminal, a television, a notebook computer, a tablet computer, a desktop computer, a game machine, a smart watch and the like.
The display device generally includes a control circuit, which may include one or more microprocessors, image processors, display driver integrated circuits, and the like. In the embodiment of the present application, the control circuit may be configured to run software in the display device, such as an operating system function; meanwhile, the system is also provided with an image processing functional module for image enhancement. The operating system of the display device is generally responsible for controlling the turning on of the image enhancement function module and the configuration of the enhancement strategy of the image to be displayed, and the image enhancement function module performs enhanced display on the image according to the enhancement strategy.
Because the operating system generally has a security mechanism, the information of the currently displayed image is not sent to the image enhancement module, and the content to be displayed is not read, so that hackers or malicious software are prevented from acquiring the information in the screen. Therefore, it is necessary for the image enhancement function module to identify whether the image to be displayed is an OSD image, so that when the image to be displayed is an OSD image, the operating system can adjust the image enhancement policy in time to avoid a negative display effect of the OSD image during display.
The OSD image may be understood as a rectangular menu for displaying various adjustment items of the display popped up from the screen, and the user may adjust the display operation indexes including color, mode, geometric shape, etc. through the menu, thereby achieving the best usage state. For example, by displaying special glyphs or graphics on the display, the user is given messages.
Because the OSD image is generally characterized by a large-area structure of a solid background and a character icon to represent a specific function, and the information amount is limited, in the embodiment of the application, whether the displayed image is the OSD image is determined by using the histogram of at least two dimensions, the identification of the OSD image can be effectively realized, and the identification accuracy is high; meanwhile, the enhancement display is carried out through the enhancement strategy corresponding to the identification result, and the problem of negative display effect when the display image is an OSD image can be effectively avoided.
Specifically, referring to fig. 1, fig. 1 is a schematic flow chart of an image processing method provided in an embodiment of the present application, where in the embodiment of the present application, the image processing method includes:
s101, acquiring a first image to be processed.
In the embodiment of the present application, the image processing method is implemented by an image processing apparatus in a display device, the image processing apparatus belongs to a program module and is stored in a memory capable of calling the program by an image enhancement module, and the image processing apparatus is called by the image enhancement module to implement the image processing method.
In one possible implementation, the image enhancement module is a hardware module, and is integrated on an integrated circuit chip, and is used for improving picture quality, such as improving picture contrast, improving brightness, enhancing details, and the like.
In the embodiment of the present application, a first image to be processed is obtained, and the first image may be an image to be displayed in a display device.
S102, carrying out image processing on the first image, obtaining at least one second image, and carrying out statistics on histograms of the second image in at least two dimensions.
In the embodiment of the present application, the first image may be subjected to image processing to obtain at least one second image, where the image processing includes, but is not limited to, a cropping process, a region dividing process, and the like of the first image. And after at least one second image is obtained, histograms of each second image in at least two dimensions can be respectively counted.
Among them, there are various dimensions of images, such as: gray scale, luminance, chrominance, saturation, gradient, noise, etc., any two or more dimensions of which may be selected, and a histogram of the second image in the any two or more dimensions is counted.
S103, identifying whether the first image is an OSD image according to the histogram of the second image in each dimension.
It can be understood that, while natural images tend to have rich texture, detail and color and contain rich information, OSD images are generally monotonous and are the structure of the pure background frame text icons, and the amount of information is limited. And because the histogram can represent the information content of the image in the corresponding dimension, whether the first image is the OSD image can be identified in a histogram statistical mode, and the accuracy of the OSD image identification can be effectively improved by using the histogram of at least two dimensions.
And S104, enhancing and displaying the first image by utilizing an enhancement strategy corresponding to the identification result of the first image.
In the embodiment of the application, after the first image is identified, the identification result of whether the first image is the OSD image can be obtained, so that the enhancement display can be performed on the first image by using the enhancement strategy corresponding to the identification result of the first image.
Illustratively, when the first image is a non-OSD image, the first image is enhanced and displayed by using an initial enhancement strategy configured by an operating system; when the first image is an OSD image, an initial enhancement strategy configured without using an operating system may be selected, that is, the first image is not enhanced and displayed, or the initial enhancement strategy is adjusted, for example, the image enhancement intensity is reduced; when the first image is a partial OSD image, the initial enhancement policy configured by the operating system may be adjusted by using a preset adjustment function to obtain an adjusted corresponding enhancement policy, and the first image is enhanced and displayed according to the adjusted corresponding enhancement policy.
In the embodiment of the application, at least one second image is obtained by performing image processing on the obtained first image, histograms of the second images in at least two dimensions are respectively counted, whether the first image is an OSD image can be identified according to the histograms of the second images in the dimensions, and then an enhancement strategy corresponding to the identification result is used for enhancing and displaying the first image. Whether the first image is the OSD image or not is determined by using the histograms of at least two dimensions, the identification of the OSD image can be effectively realized, the identification accuracy is high, meanwhile, the first image is subjected to enhancement display by using an enhancement strategy corresponding to the identification result of the first image, and the problem of negative display effect when the first image is the OSD image can be avoided.
Based on the content described in the foregoing embodiment, please refer to fig. 2, fig. 2 is a schematic flowchart of a second image processing method provided in an embodiment of the present application, in another possible embodiment of the present application, the image processing method includes:
s201, acquiring a first image to be processed.
S202, carrying out image processing on the first image, obtaining at least one second image, and carrying out statistics on histograms of the second image in at least two dimensions.
In this embodiment of the present application, after acquiring a first image, the first image may be subjected to image processing to acquire at least one second image, and one possible implementation manner is as follows:
and A, acquiring a display position parameter of a display interface control of the display equipment.
And step B, cutting the first image by using the display position parameters to obtain a cut first image.
And step C, performing area division on the cut first image to obtain at least one second image.
In this embodiment, it is considered that when the display interface of the user equipment displays the image, some user interface controls exist, which are always displayed and are not changed in position, for example, for a mobile terminal, the existing user interface controls with fixed positions include a status bar, a sliding bar, a bottom button or a picture-in-picture, and the like. The display position parameter of the user interface control can be obtained, the display position parameter is usually fixed and the size of the display position parameter is not changed, and the first image is cut by using the display position parameter, so that the cut first image is obtained.
It can be understood that the characteristics of the display image of the user interface control are similar to those of the OSD image, the first image is cut, the display image of the user interface control with the fixed display position parameters is cut, the interference of the display image of the user interface control in identifying the OSD image can be avoided, and the accuracy of OSD image identification is improved.
It can be understood that, if the first image is not displayed with the display image of the user interface control, the step a and the step B need not be executed, and therefore, in practical applications, it may be determined whether the first image needs to be cropped according to practical needs.
For better understanding of the embodiment of the present application, please refer to fig. 3, and fig. 3 is a schematic diagram of performing image processing on a first image according to the embodiment of the present application.
In fig. 3, image 1 represents a first image to be processed; image 2 represents the cropped first image; image 3 represents the second image.
Each second image can be located at any position in the screen, and the size and the length-width ratio of each second image can be flexibly set.
Further, considering that the OSD image may only occupy a portion of the display interface when displayed, for example, when a user uses a user device to view a video, an OSD image pops up and is superimposed in a scene of the video image, the first image will include the OSD image and a portion of the video image, and the portion of the video image will interfere with the identification of the OSD image, thereby reducing the accuracy of the identification of the OSD image.
S203, acquiring information entropy of the histograms of the second image in each dimension by using the histogram of the second image in each dimension.
In the embodiment of the application, histograms of each second image in at least two dimensions are respectively counted; and acquiring the information entropy of each dimension histogram of each second image by using the histogram of each second image in each dimension.
In information theory, information within a system is quantized, typically using information entropy. By using the concept of thermodynamics, shannon refers to the information amount with redundancy removed from the information as the information entropy.
Taking the used dimensions including brightness and chroma as an example, the brightness histogram HL of each second image can be countediAnd a chrominance histogram HCiDividing the number of pixel points of each brightness in the histogram of the second image by the number of all pixel points in the second image to obtain the probability PL corresponding to the corresponding brightnessiIn the same way, the number of the pixel points of each chroma in the histogram of the second image is divided by the number of all the pixel points in the second image to obtain the probability PC corresponding to the corresponding chromaiFurther, the information entropy of the luminance histogram and the information entropy of the chrominance histogram are calculated as follows:
wherein TL is the information entropy of the luminance histogram of the second image, TC is the information entropy of the chrominance histogram of the second image, i represents the abscissa of the histogram, the luminance is usually divided into 256 steps, and the chrominance is usually divided into 360 steps.
And S204, identifying whether the first image is an OSD image according to the information entropy of the histogram of the second image in each dimension.
And S205, performing enhancement display on the first image by using an enhancement strategy corresponding to the identification result of the first image.
In this embodiment of the application, after obtaining the information entropy of each dimension histogram of the second image, whether the first image is an OSD image is identified by using the information entropy of each dimension histogram, and the specific method may include the following steps:
step one, calculating the product of the information entropies of the histograms of the second image in all dimensions to obtain the confidence parameter of the second image.
And step two, obtaining the recognition result of the second image according to the confidence parameter of the second image.
And step three, determining whether the first image is an OSD image according to the identification result of the second image.
In the embodiment of the present application, a product of information entropies of the histograms of the dimensions of the second image is calculated to obtain a confidence parameter of the second image, for example, if the information entropy of the luminance histogram of the second image is TL and the information entropy of the chrominance histogram is TC, the information entropy of the second image is TL × TC, that is, the confidence parameter of the second image, and the recognition result of the second image can be obtained according to the confidence parameter of the second image.
Specifically, whether the confidence parameter of the second image is greater than a preset first threshold value is judged, if the confidence parameter is greater than the first threshold value, the second image is determined to be a non-OSD image, and if the confidence parameter is less than or equal to the first threshold value, the second image is determined to be an OSD image. It can be understood that, when the number of the second images is 1, the recognition result of the second image is the recognition result of the first image, and when the number of the second images is greater than 1, it is necessary to determine whether the first image is an OSD image according to the recognition results of the plurality of second images.
In an implementation manner, considering that the confidence parameter of the second image is closer to the first threshold, the second image may or may not be an OSD image, and therefore, before determining whether the confidence parameter of the second image is greater than the preset first threshold, it may also be determined whether the absolute value of the difference between the confidence parameter of the second image and the preset first threshold is greater than the second threshold.
If the absolute value is larger than the second threshold, continuously judging whether the confidence parameter of the second image is larger than a preset first threshold. If the absolute value is less than or equal to the second threshold, it indicates that the difference between the confidence parameter of the second image and the first threshold is not large, in order to improve the accuracy of identifying the second image, a target dimension may be selected from a preset candidate dimension set, and the information entropy of the histogram of the second image in the target dimension is obtained, where the calculation method of the information entropy is similar to the calculation method of the chrominance and luminance information entropy, and is not described herein again.
The candidate dimension set includes other dimensions except for the used dimension, for example: if the dimensions include: gray scale, luminance, chrominance, saturation, gradient, and noise, where the used dimensions include luminance and chrominance, and the set of candidate dimensions includes gray scale, saturation, and noise. In the selection, the target dimension may be randomly selected, or selected according to a preset sequence, and in practical application, the selection mode of the target dimension may be set according to specific needs, which is not limited herein.
After the information entropy of the histogram of the second image in the target dimension is obtained, the above-mentioned product of the information entropies of the histograms of the dimensions of the second image is calculated, and the confidence parameter of the second image is obtained.
Optionally, if the absolute value of the difference between the confidence parameter obtained by the second image based on the product of the information entropy of the histograms of the dimension a and the dimension B and the first threshold is smaller than the second threshold, the information entropy of the histogram of the dimension C is obtained, the information entropy of the histogram of the dimension a, the information entropy of the histogram of the dimension B, and the information entropy of the histogram of the dimension C are multiplied to obtain an updated confidence parameter, and the identification result of the second image is obtained according to the updated confidence parameter. Comparing the absolute value of the difference value between the updated confidence parameter and the first threshold with a second threshold, when the absolute value is smaller than or equal to the second threshold, adding a new target dimension until the absolute value is larger than the second threshold, continuously judging whether the confidence parameter of the second image is larger than the preset first threshold, when the confidence parameter of the second image is larger than the preset first threshold, determining that the second image is a non-OSD image, and when the confidence parameter of the second image is smaller than the preset first threshold, determining that the second image is an OSD image.
For better understanding of the embodiment of the present application, refer to fig. 4, where fig. 4 is a schematic flowchart of a refinement step of step two in the above embodiment of the present application, and includes:
s401, judging whether the absolute value of the difference value between the confidence parameter of the second image and the first threshold value is larger than a preset second threshold value or not; if yes, continue to execute step S402; if not, go to step S405.
S402, judging whether the confidence parameter of the second image is larger than a preset first threshold value or not; if yes, continue to execute step S403; if not, go to step S404.
And S403, determining that the second image is a non-OSD image.
S404, determining the second image as an OSD image.
S405, selecting a target dimension from a preset candidate dimension set, and acquiring the information entropy of the histogram of the second image in the target dimension.
S406, calculating the product of the information entropies of the histograms of the second image in all dimensions including the target dimension to obtain a new confidence parameter of the second image.
S407, judging whether the new confidence parameter of the second image is larger than a preset first threshold value or not; if yes, go on to step S408; if not, step S409 is executed.
S408, determining that the second image is a non-OSD image.
And S409, determining the second image as an OSD image.
In the embodiment of the present application, after confirming whether each second image is an OSD image through the confidence parameter, whether the first image is an OSD image is determined according to the recognition result of the second image.
Specifically, if the number of the second images is one, determining that the identification result of the second image is the identification result of the first image; that is, when the number of the second images is one, if the second images are OSD images, the first images are also OSD images, and if the second images are non-OSD images, the first images are non-OSD images.
If the number of the second images is at least two, determining the first image as an OSD image when the identification results of all the second images are OSD images; when the identification results of all the second images are non-OSD images, determining that the first image is a non-OSD image; and if the identification result of the partial second image is the OSD image, determining that the first image is the partial OSD image. The partial OSD image means that the image in a partial area in the first image is the OSD image.
Further, after determining the recognition result of the first image, the first image may be enhanced and displayed by using an enhancement policy corresponding to the recognition result of the first image, and in a feasible implementation manner, when the first image is a non-OSD image, the first image may be enhanced and displayed by using a first image enhancement intensity; when the first image is a partial OSD image, the first image can be subjected to enhanced display by adopting a second image enhancement intensity; when the first image is an OSD image, the first image may be enhanced and displayed with a third image enhancement intensity; and the second image enhancement intensity is smaller than the first image enhancement intensity and larger than the third image enhancement intensity.
For example, if the first image is an OSD image, the function of enhancing the display may be turned off, or a preset correspondence between the information entropy of the OSD image and the enhancement strength is searched to determine the enhancement strength of the OSD image, where the enhancement strength is generally inversely proportional to the information entropy. If the first image is a non-OSD image, the enhancement is performed according to an enhancement strategy configured by an operating system, and if the first image is a partial OSD image, the intensity of the enhancement can be adjusted based on the determined proportion of the natural image in the first image. For example, if there are four second images, two of which are OSD images and the other two of which are non-OSD images, the enhancement display effect can be reduced to half of the effect corresponding to the enhancement policy.
In the embodiment of the application, the first image is cut and divided into regions, so that the influence of a user interface control on the accuracy of the OSD image recognition can be avoided, the confidence parameter obtained by using the information entropy of the histograms of at least two dimensions of at least one second image is used for recognizing the OSD image, and the accuracy of the OSD image recognition can be effectively improved. And the first image is enhanced and displayed by utilizing the enhancement strategy corresponding to the identification result of the first image, so that the problem of negative display effect when the first image is an OSD image can be avoided.
Based on the content described in the above embodiments, an image processing apparatus is also provided in the embodiments of the present application. Referring to fig. 5, fig. 5 is a schematic diagram of functional modules of an image processing apparatus according to an embodiment of the present application, where the image processing apparatus 50 includes:
an obtaining module 501 is configured to obtain a first image to be processed.
A processing module 502, configured to perform image processing on the first image, obtain at least one second image, and count histograms of the second image in at least two dimensions.
The identifying module 503 is configured to identify whether the first image is an OSD image of an on screen display menu according to the histogram of the second image in each dimension.
And an enhancement module 504, configured to perform enhanced display on the first image by using an enhancement policy corresponding to the identification result of the first image.
In the embodiment of the application, whether the first image is the OSD image or not is determined by using the histograms of at least two dimensions, the identification of the OSD image can be effectively realized, the identification accuracy is high, and meanwhile, the problem of negative display effect when the first image is the OSD image can be avoided by utilizing the enhancement strategy corresponding to the identification result of the first image to perform enhanced display on the first image.
Further, based on the content described in the foregoing embodiments, the present application also provides a display device, where the display device includes at least one processor and a memory; wherein the memory stores computer execution instructions; the at least one processor executes computer-executable instructions stored in the memory to implement the content described in the embodiments of the image processing method.
The display device provided in this embodiment may be used to implement the technical solutions of the above method embodiments, and the implementation principles and technical effects are similar, which are not described herein again.
For better understanding of the embodiments of the present application, referring to fig. 6, fig. 6 is a schematic diagram of a hardware structure of a display device provided in the embodiments of the present application.
As shown in fig. 6, the display device 60 of the present embodiment includes: a processor 601 and a memory 602; wherein
A memory 602 for storing computer-executable instructions;
the processor 601 is configured to execute the computer execution instructions stored in the memory to implement the steps performed by the display device in the foregoing embodiments. Reference may be made in particular to the description relating to the method embodiments described above.
Alternatively, the memory 602 may be separate or integrated with the processor 601.
When the memory 602 is provided separately, the device further comprises a bus 603 for connecting said memory 602 and the processor 601.
Embodiments of the present application further provide a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when a processor executes the computer-executable instructions, the steps performed by the user equipment in the above embodiments are implemented.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules is only one logical division, and other divisions may be realized in practice, for example, a plurality of modules may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present application may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in the incorporated application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (11)
1. An image processing method, characterized in that the method comprises:
acquiring a first image to be processed;
performing image processing on the first image to obtain at least one second image, and counting histograms of the second image in at least two dimensions;
identifying whether the first image is an OSD image of a screen display menu according to the histogram of the second image in each dimension;
enhancing and displaying the first image by utilizing an enhancement strategy corresponding to the identification result of the first image;
the identifying whether the first image is an OSD image according to the histogram of the second image in each dimension includes:
acquiring information entropy of the histograms of the second images in all dimensions by utilizing the histograms of the second images in all dimensions;
and identifying whether the first image is an OSD image according to the information entropy of the histogram of the second image in each dimension.
2. The method according to claim 1, wherein the identifying whether the first image is an OSD image according to the information entropy of the histogram of the second image in each dimension comprises:
calculating the product of the information entropies of the histograms of the dimensions of the second image to obtain a confidence parameter of the second image;
obtaining an identification result of the second image according to the confidence parameter of the second image;
and determining whether the first image is an OSD image according to the identification result of the second image.
3. The method according to claim 2, wherein obtaining the recognition result of the second image according to the confidence parameter of the second image comprises:
judging whether the confidence parameter of the second image is larger than a preset first threshold value or not;
if the confidence parameter is larger than the first threshold value, determining that the second image is a non-OSD image;
and if the confidence parameter is less than or equal to the first threshold value, determining that the second image is an OSD image.
4. The method of claim 3, wherein before determining whether the confidence parameter of the second image is greater than a preset first threshold, further comprising:
judging whether the absolute value of the difference value between the confidence parameter of the second image and the first threshold value is larger than a preset second threshold value or not;
the determining whether the confidence parameter of the second image is greater than a preset first threshold value includes:
if the absolute value is larger than the second threshold, judging whether the confidence parameter of the second image is larger than a preset first threshold.
5. The method of claim 4, further comprising:
if the absolute value is smaller than or equal to the second threshold, selecting a target dimension from a preset candidate dimension set, and acquiring the information entropy of the histogram of the second image in the target dimension;
calculating the product of the information entropies of the histograms of the second image in all dimensions including the target dimension to obtain a new confidence parameter of the second image;
obtaining a new recognition result of the second image according to the new confidence parameter of the second image;
and determining whether the first image is an OSD image or not according to the new identification result of the second image.
6. The method of claim 2, wherein the determining whether the first image is an OSD image according to the recognition result of the second image comprises:
if the number of the second images is one, determining that the identification result of the second images is the identification result of the first images;
if the number of the second images is at least two, determining that the first image is an OSD image when the identification results of all the second images are OSD images; when the identification results of all the second images are non-OSD images, determining that the first image is a non-OSD image; and when the identification result of the partial second image is the OSD image, determining that the first image is the partial OSD image.
7. The method according to any one of claims 1 to 6, wherein the enhancing the first image by using the enhancement policy corresponding to the recognition result of the first image comprises:
when the first image is a non-OSD image, enhancing and displaying the first image by adopting first image enhancement intensity;
when the first image is a partial OSD image, enhancing and displaying the first image by adopting second image enhancement intensity;
when the first image is an OSD image, enhancing and displaying the first image by adopting a third image enhancement intensity;
wherein the second image enhancement intensity is less than the first image enhancement intensity and greater than the third image enhancement intensity.
8. The method according to any one of claims 1 to 6, wherein the image processing the first image to obtain at least one second image comprises:
acquiring display position parameters of a display interface control of display equipment;
cutting the first image by using the display position parameter to obtain a cut first image;
and carrying out region division on the cut first image to obtain at least one second image.
9. An image processing apparatus, characterized in that the apparatus comprises:
the acquisition module is used for acquiring a first image to be processed;
the processing module is used for carrying out image processing on the first image, acquiring at least one second image and counting histograms of the second image in at least two dimensions;
the identification module is used for identifying whether the first image is an OSD (on screen display) image of the screen display menu according to the histogram of the second image in each dimension;
the enhancement module is used for enhancing and displaying the first image by utilizing an enhancement strategy corresponding to the identification result of the first image;
the identification module is specifically configured to:
acquiring information entropy of the histograms of the second images in all dimensions by utilizing the histograms of the second images in all dimensions;
and identifying whether the first image is an OSD image according to the information entropy of the histogram of the second image in each dimension.
10. A display device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the image processing method of any of claims 1 to 8.
11. A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the image processing method according to any one of claims 1 to 8.
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