CN111247800A - Method and device for determining image information quantity - Google Patents

Method and device for determining image information quantity Download PDF

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CN111247800A
CN111247800A CN201980005223.8A CN201980005223A CN111247800A CN 111247800 A CN111247800 A CN 111247800A CN 201980005223 A CN201980005223 A CN 201980005223A CN 111247800 A CN111247800 A CN 111247800A
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pixel point
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CN111247800B (en
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赵文军
郝开元
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SZ DJI Technology Co Ltd
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Abstract

A method and apparatus for determining an amount of image information are provided, the method including: acquiring a first image to be processed, wherein the first image comprises first pixel points; when the image complexity of the first pixel point is larger than a threshold value, determining that the value of the image information content of the first pixel point is a first value, wherein the first value is smaller than the image complexity of the first pixel point, and the threshold value is smaller than or equal to 2P‑QP is the bit depth of the first picture, Q is a positive integer less than P. The method can determine the more appropriate image information quantity, thereby realizing more reasonable code rate distribution and further improving the coding quality.

Description

Method and device for determining image information quantity
Copyright declaration
The disclosure of this patent document contains material which is subject to copyright protection. The copyright is owned by the copyright owner. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the patent and trademark office official records and records.
Technical Field
The present application relates to the field of video encoding and decoding, and more particularly, to a method and apparatus for determining an amount of image information.
Background
Rate control controls the output stream in video communication and streaming media transmission to meet the constraints of channel bandwidth and buffer, and on the basis of the constraints, the distortion of video quality is guaranteed to be minimum as much as possible. The rate control has two steps, the first step is to allocate the rate and the second step is to calculate the quantization parameter. And for the image to be processed, the encoder encodes the image to be processed according to the code rate distributed to the image to be processed and the calculated quantization parameter. Wherein, the code rate allocation determines the quality of the coding to a great extent.
Generally, according to the image information amount of the image to be processed, a code rate is allocated to the image to be processed. Therefore, the determination of the amount of image information also determines the quality of the encoding.
Currently, in the field of video encoding and decoding, a more common method for determining the image information amount is to obtain the image information amount by calculating an edge detection operator of a pixel value of an image to be processed.
However, the edge detection operator is sensitive to the boundary information of the image, and for example, the more complex the contour in the image, the larger the value of the image information amount calculated by the edge detection operator. Practice shows that the image information amount obtained through calculation of the edge detection operator cannot accurately express the real information amount of the image.
An inappropriate amount of picture information may lead to an unreasonable code rate allocation, which may degrade the coding quality.
Disclosure of Invention
The application provides a method and a device for determining image information quantity, which can determine more appropriate image information quantity, thereby realizing more reasonable code rate distribution and further improving the coding quality.
In a first aspect, a method of determining an amount of image information is provided, the method comprising: acquiring a first image to be processed, wherein the first image comprises first pixel points; when the image complexity of the first pixel point is larger than a threshold value, determining that the value of the image information content of the first pixel point is a first value, wherein the first value is smaller than the image complexity of the first pixel point, and the threshold value is smaller than or equal to 2P-QP is the bit depth of the first picture, Q is a positive integer less than P.
In a second aspect, an encoding apparatus is provided, which includes: the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a first image which comprises a first pixel point; a determining unit, configured to determine that a value of an image information amount of the first pixel is a first value when the image complexity of the first pixel is greater than a threshold, where the first value is smaller than the image complexity of the first pixel, and the threshold is less than or equal to 2P-QP is the bit depth of the first picture, Q is a positive integer less than P.
In a third aspect, an encoding apparatus is provided, which includes a memory for storing instructions and a processor for executing the instructions stored in the memory, and the execution of the instructions stored in the memory causes the processor to execute the method in the implementation manner of the first aspect.
In a fourth aspect, a chip is provided, where the chip includes a processing module and a communication interface, where the processing module is configured to control the communication interface to communicate with the outside, and the processing module is further configured to implement the method in the implementation manner of the first aspect.
In a fifth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a computer, causes the computer to carry out the method in the implementation of the first aspect.
In a sixth aspect, there is provided a computer program product comprising instructions which, when executed by a computer, cause the computer to carry out the method in the implementation of the first aspect.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image to a certain extent, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved. In other words, the method and the device can determine the more appropriate image information amount, thereby realizing more reasonable code rate distribution and further improving the coding quality.
Drawings
Fig. 1 is a schematic diagram of an application scenario of the present application.
Fig. 2 is a schematic flow chart of a method for determining image information amount according to an embodiment of the present application.
Fig. 3 is another schematic flow chart of a method for determining image information amount according to an embodiment of the present application.
Fig. 4 is a further schematic flowchart of a method for determining an amount of image information according to an embodiment of the present application.
Fig. 5 is a schematic diagram illustrating an appearance frequency of a value of image complexity of each pixel point in a statistical image according to an embodiment of the present application.
Fig. 6 is still another schematic flowchart of a method for determining an amount of image information according to an embodiment of the present application.
Fig. 7 is a schematic structural diagram of an encoding apparatus according to an embodiment of the present invention.
Fig. 8 is a schematic structural diagram of an encoding apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
Fig. 1 is a schematic diagram of an application scenario of the present application. As shown in fig. 1, in the process of encoding a large-size image, the whole image is divided into a plurality of image blocks, each image block is encoded in sequence to obtain a corresponding code stream (such as a partial code stream described in fig. 1), and finally, all the partial code streams are processed to output a final total code stream.
Before each image block is coded, the available code stream of each image block needs to be determined, that is, the code rate of each image block is allocated. When the code rate allocated to each image block is appropriate, a better image coding effect can be achieved.
In general, a code rate is assigned to an image block based on the amount of image information for the image block. Therefore, before performing rate allocation on an image block, the image information amount of the image block needs to be measured.
It is to be understood that the amount of image information of an image refers to an amount of information measured based on pixel values of the image.
Taking the image block shown in fig. 1 as an example, the method for acquiring the image information amount of an image block is to acquire the image information amount of the image block by calculating an edge detection operator of the pixel value of the image block. The edge detection operators comprise Roberts operators, Sobel operators, Prewitt operators, Laplace operators, Canny operators and the like.
However, the edge detection operator is sensitive to the boundary information of the image, and for example, the larger the amount of boundary information in the image, the larger the value of the amount of information calculated by the edge detection operator. However, in the actual use process, it is found that the value of the information amount calculated by the edge detection operator cannot accurately describe the true information amount of the image. For example, for a region with a complex contour in an image, the value of the image information amount obtained by the edge detection operator far exceeds the real information amount contained in the region.
Therefore, the existing edge detection operator technology cannot accurately determine the image information amount, or cannot acquire an appropriate image information amount.
For an image block, if the amount of image information is determined to be inappropriate, the allocated code rate for the image block is inappropriate, and the coding quality is poor.
In view of the above problems, the present application provides a method and an apparatus for determining an image information amount, which can determine a more appropriate image information amount, so as to implement more reasonable code rate allocation, and further improve coding quality.
The method and the device can be applied to the field of image coding. For example, the scheme provided by the present application can be applied to an encoder that conforms to any one of the following standards: h.264/Advanced Video Coding (AVC) standard, h.265/High Efficiency Video Coding (HEVC) standard, h.266/multi-function video coding (VVC), and source coding standard (AVS).
The first image to be processed in the embodiment of the present application may be one frame image.
The first image to be processed in the embodiment of the present application may also be an image block in one frame image, for example, the image block shown in fig. 1. For another example, the image block may be a Coding Tree Unit (CTU) in the h.265 standard, or a macroblock (macro block) or a Largest Coding Unit (LCU) in the h.264 standard.
Fig. 2 is a schematic flow chart of a method 200 for determining an amount of image information according to an embodiment of the present application. The method 200 may be performed by an encoder, for example. The method 200 includes the following steps 210 and 220.
And 210, acquiring a first image to be processed, wherein the first image comprises a first pixel point.
220，When the image complexity of the first pixel point is larger than a threshold value, determining that the value of the image information content of the first pixel point is a first value, wherein the first value is smaller than the image complexity of the first pixel point, and the threshold value is smaller than or equal to 2P-QP is the bit depth of the first picture, Q is a positive integer less than P.
The image information amount of the first pixel point is determined based on the image complexity of the first pixel point.
The image complexity of the first pixel point may be determined based on the pixel value of the first pixel point. For example, the image complexity of the first pixel point may be determined according to the Image Activity (IAM) of the first pixel point.
As an example, the Image Complexity (ICS) of the first pixel point is determined according to the following formula:
ICS＝IAMpixel(I, j) ═ I (I, j) -I (I +1, j) | + | I (I, j) -I (I, j +1) | formula (1)
Wherein, (I, j) represents the position of the first pixel point in the first image, I (I +1, j) represents the pixel value of the pixel point with the position of (I +1, j), and I (I, j +1) represents the pixel value of the pixel point with the position of (I, j + 1).
The image complexity of the first pixel point can also be obtained by adopting other feasible modes, which is not limited in the application.
As described above, in some cases, the contour in an image is complicated, but the amount of information contained in the image is not necessarily large. The value of the image complexity of a pixel point located in an area with a more complex outline in an image may also be larger, and if the image complexity of the pixel point is taken as the image information amount of the pixel point, the image information amount of the pixel point is also larger, so that the image information amount of the image determined based on the image information amount of each pixel point is also larger. This may occur in a case where the value of the image information amount of the image greatly differs from the information amount contained in the image.
In order to avoid such a situation as much as possible, in the present application, in the process of determining the image information amount of the first pixel point, when the image complexity of the first pixel point is greater than the threshold, the value of the image information amount of the first pixel point is made smaller than the image complexity of the first pixel point.
It should be understood that the image information amount of the first image may be determined according to the image information amounts of some or all pixel points in the first image, for example, the sum of the image information amounts of all pixel points in the first image is used as the image information amount of the first image.
In the process of determining the image information amount of each pixel point in the first image, if the image complexity of the pixel point is greater than the threshold value, the value of the image information amount of the pixel point is smaller than the image complexity of the pixel point. This makes it possible to make the amount of image information of the first image as close as possible to the amount of image information actually contained in the first image. Therefore, the following situations existing in the prior art can be avoided to a certain extent: for a region with a complex contour in an image, the determined value of the image information content far exceeds the real information content contained in the region.
According to the more appropriate image information quantity, the appropriate code rate can be allocated to the first image, so that the encoding quality can be improved.
The image complexity of the first pixel point is measured by adopting a threshold value, and when the image complexity is larger than the threshold value, the image information amount of the first pixel point is smaller than the image complexity. The threshold may be equal to 2P-QAlternatively, the threshold may be less than 2P-QIs an integer of less than or equal to 2P-QP is the bit depth of the first picture, Q is a positive integer less than P.
It should be understood that it is reasonable to measure the image complexity of the first pixel point by a threshold value associated with the bit depth of the first image.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image to a certain extent, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved.
It should be understood that the bit depth of an image refers to the number of bits used to store each pixel in the image. The bit depth of an image determines the maximum number of colors that can be present in a color image, or the maximum gray scale level in a gray scale image. For example, for a monochrome image, the maximum gray scale is 2 to the power of 8, i.e., the number of bits used to store each pixel is 8, i.e., the bit depth of the image is 8 bits. As another example, for a bayer image, each pixel position has only one color component, and the number of bits used for each pixel is 12, i.e., the bit depth of the image is 12 bits.
In the embodiment of the present application, the bit depth P of the first image may be 8, 10, 12, 14, 16, or the like. Q is a positive integer less than P. For example, Q is equal to 3, 4, or 5.
As will be described later, when the image complexity of the first pixel is greater than the threshold, how to determine the value of the image information amount of the first pixel so that the value is smaller than the image complexity of the first pixel.
Optionally, as an implementation manner of step 220, when the image complexity of the first pixel is greater than the threshold, the value of the image information amount of the first pixel is determined according to the threshold and the image complexity of the first pixel, so that the value of the image information amount of the first pixel is smaller than the image complexity of the first pixel.
For example, according to a linear combination of the threshold and the image complexity of the first pixel point, the value of the image information amount of the first pixel point is determined to be smaller than the image complexity of the first pixel point.
As an example, the value V of the image information amount of the first pixel point may be determined according to the following formula:
v is a.ICS + b.Thr type (2)
The ICS represents the image complexity of the first pixel point, Thr represents a threshold, a and b are constants, a is a positive number smaller than 1, and the sum of a and b is equal to 1.
For example, a equals 0.15 and b equals 0.85. Alternatively, a equals 0.05 and b equals 0.95.
Optionally, as another implementation manner of step 220, when the image complexity of the first pixel is greater than the threshold, a difference between the image complexity of the first pixel and a preset value is used as the value of the image information amount of the first pixel.
The preset value may be an empirical value or a value determined according to specific requirements. For example, practical experience shows that, for a more complex image block, if the image complexity is directly used as the image information amount of the image block, such image information amount is x units larger than the information amount actually contained in the image block, and therefore, the preset value can be determined according to the x units.
It should be understood that, in addition to the above manners, other feasible manners may be adopted to determine the value of the image information amount of the first pixel point so as to be smaller than the image complexity of the first pixel point when the image complexity of the first pixel point is greater than the threshold.
It should be further understood that, in practice, the image complexity of the first pixel point may also be less than or equal to the threshold, in this case, as shown in fig. 3, the method 200 further includes a step 230, when the image complexity of the first pixel point is less than or equal to the threshold, determining that the value of the image information amount of the first pixel point is a second value, and the second value is equal to or greater than the image complexity of the first pixel point.
Optionally, when the image complexity of the first pixel point is less than or equal to the threshold, it is determined that the value of the image information amount of the first pixel point is equal to the image complexity of the first pixel point.
Optionally, when the image complexity of the first pixel point is less than or equal to the threshold, it is determined that the value of the image information amount of the first pixel point is greater than the image complexity of the first pixel point.
For example, the value of the image information amount of the first pixel point is determined to be equal to an integer multiple of the image complexity of the first pixel point, and the integer multiple may be determined according to an empirical value or according to actual application requirements.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is smaller than the threshold, the value of the image information amount of the pixel point is set to be equal to or larger than the image complexity of the pixel point, and when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image as much as possible, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved.
In addition, the value of the image information amount of the pixel point with larger image complexity is set to be smaller than the image complexity of the pixel point, so that the image information amount of the final image can be ensured not to be large to a certain extent, the code rate allocated to the image can be ensured not to be large, and when the image is coded, the compression ratio of each image slice can not generate overlarge fluctuation, and the coding quality can be ensured.
It should be noted that, for convenience of understanding and description, the first pixel point in the first image is taken as an example for description in the embodiment of the present application, but this does not limit the embodiment of the present application. First, the expression "first" in the first pixel point is only for convenience of description and distinction, and is not used to limit the scope of the embodiment of the present invention, and the first pixel point may represent any pixel point in the first image. Secondly, for any pixel point in the first image, the method provided by the embodiment of the application can be adopted to determine the image information amount.
The manner of determining the threshold will be described below.
Optionally, in some embodiments, as shown in fig. 4, the method 200 further comprises step 240 and step 250.
And 240, acquiring a reference value, wherein the reference value is the image complexity value of one pixel point in the second image. The second image is the first image, or the second image is a previous frame image of the first image.
Optionally, the reference value is an image complexity of a certain pixel point in the first image.
Alternatively, when the first image is a frame of image in the video stream, the reference value may be an image complexity of a pixel point in a frame of image before the first image.
Optionally, the reference value may be an image complexity of any pixel point in the second image.
Optionally, the reference value may be an image complexity of a pixel point in the second image, where the image complexity is closest to a preset value.
Optionally, the reference value may be an image complexity of a pixel point in the second image that satisfies a preset condition. This will be described in detail below.
250 when the reference value is less than 2P-QWhen the threshold value is determined to be equal to the reference value; when the reference value is greater than or equal to 2P-QWhen the threshold is determined to be equal to 2P-Q。
Optionally, in this embodiment, when the threshold is equal to the reference value, a in the above equation (2) is 0.15. When the threshold is equal to 2P-QIn this case, a in the above formula (2) is 0.05.
The present embodiment can be applied to a still image as well as a moving image. For example, the first image referred to in this embodiment is a still image, or a moving image, i.e., a series of still images in a video stream.
Optionally, in an embodiment involving a reference value, the reference value satisfies the following condition:
and for the image complexity of each pixel point in the second image, performing multiplication and accumulation on the value of each image complexity and the occurrence frequency thereof from the image complexity with the lowest value until the multiplication and accumulation result is equal to or more than k times of the image complexity of the second image, and finally performing the multiplication and accumulation on the value of the image complexity as the reference value.
Wherein k is a constant and k is a positive number less than 1. As an example, k is equal to 0.5. It is understood that k can also be other positive numbers less than 1, e.g., any number from 0.4 to 0.6.
Optionally, in some embodiments, the second image is the first image, wherein step 240 may include: starting from the lowest image complexity in the values of the image complexities, performing multiply-accumulate on each value and the occurrence frequency thereof until the multiply-accumulate result is equal to or more than k times of the image complexity of the first image; and taking the value of the image complexity subjected to multiply accumulation finally as the reference value.
For example, the reference value S is determined according to the following formula:
Figure BDA0002457451290000091
the image complexity of the first image is represented by sum, w represents the value of the image complexity, w is increased from 0 to S, h.getvalue (w) represents the number of times that a pixel point of the image equal to w appears in the first image, sum' represents the sum of the image complexities of pixel points of which the image complexity does not exceed a reference value in the first image, k is a constant, and k is a positive number smaller than 1.
As an example, k is equal to 0.5. It is understood that k can also be other positive numbers less than 1, e.g., k is any number from 0.4 to 0.6.
For example, the image complexity sum of the first image may be obtained according to the following formula:
Figure BDA0002457451290000092
wherein the ICSpiexlAnd (i, j) represents the image complexity of the pixel point with the position (i, j) in the first image.
In this embodiment, the S value corresponding to a sum' larger than k times sum is used as the parameter value.
Optionally, in some embodiments, in step 240, a statistical histogram of the frequency of occurrence of the image complexity value of all the pixels in the first image may also be generated, as shown in fig. 5, which may be beneficial to calculate formula (3).
In fig. 5, the abscissa is the Image Complexity (ICS), w represents the value of the ICS, the ordinate is the number of occurrences (also referred to as frequency) of the value of the ICS, and h.getvalue (w) represents the number of occurrences of the ICS taking the value w in the first image.
It should be appreciated that if the reference value is available in advance, in some embodiments described above, step 240 may not be performed and step 250 may be performed directly.
The present embodiment can be applied to a still image as well as a moving image. For example, the first image referred to in this embodiment is a still image, or a moving image, i.e., a series of still images in a video stream.
Optionally, in some embodiments, the first image is a dynamic image, that is, the first image is a frame of image in a video stream, in this case, when the first image is processed, the reference value of the previous frame of image of the first image may be taken as the reference value of the first image. Corresponding to the process shown in fig. 4, the reference value in step 240 is the image complexity value of a pixel point in the previous frame image of the first image.
Optionally, the reference value may be an image complexity of any pixel point in a previous frame image of the first image.
Optionally, the reference value may be an image complexity of a pixel point of a previous frame image of the first image, where the image complexity is closest to a preset value.
Optionally, the reference value may be an image complexity of a pixel point in a previous frame of the first image, where the pixel point meets a preset condition.
For example, the reference value satisfies the following preset condition: and aiming at the image complexity of each pixel point in the previous frame of image of the first image, from the image complexity with the lowest value, performing multiplication accumulation on the value of each image complexity and the occurrence frequency thereof until the multiplication accumulation result is equal to or more than k times of the image complexity of the second image of the previous frame of image, and finally performing the multiplication accumulation on the value of the image complexity to be the reference value.
According to the embodiment of the application, for the dynamic image, the parameter value of the previous frame image is adopted to determine the threshold value for the current image to be processed, and the reference value does not need to be calculated in real time, so that the requirement on the operation speed in the encoding process of the dynamic image (namely video) can be met.
In order to facilitate directly obtaining the reference value during the processing of the next frame of image, in this embodiment, the method 200 further includes: the reference value of the currently processed first image is acquired, and for example, the reference value of the current frame is calculated according to the above formula (4).
Alternatively, in this embodiment, the reference value of the currently processed first image may be determined while performing step 240 and step 250.
It should be understood that when processing the next frame image of the current frame, the reference value of the current frame can be directly used to determine the threshold corresponding to the next frame image, which can improve the efficiency of video processing.
It should also be understood that, in a scene in which the first image is a dynamic image, when the first image is a first frame image in a video stream, the reference value may be set to a preset value when the first image is processed. The preset value may be an empirical value. For example, the preset value is 0.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image to a certain extent, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved.
An exemplary flow of applying the method of an embodiment of the present application to video encoding is described below in conjunction with fig. 6. As shown in fig. 6, the following steps are included.
The video encoding process begins.
601, judging whether the current frame is the first frame in the video stream, if yes, turning to step 602, and if not, turning to step 603.
602, the reference value S0 of the present frame is set to 0.
603, the reference value S 'stored in the image processing of the previous frame is called, and the reference value S0 of the present frame is set to S'.
604, determine if the reference value S0 of the frame is less than 2P-QIf yes, go to step 605, if no, go to step 606。
605, the parameter a is assigned to 0.15, and the process goes to step 607.
606, update the value of the reference value S0 to 2P-QThe value of parameter a is set to 0.05 and the process proceeds to step 607.
607, judging whether the image complexity ICS of the pixel point of the current frame is less than the parameter value S0, if yes, going to step 608, if no, going to step 609.
The value V of the image information amount of the pixel point is determined as the image complexity ICS of the pixel point, where V is ICS as shown in fig. 6. Go to step 610.
609, the image information amount V of the pixel point is determined according to the following formula, and go to step 610.
V ═ a + S0 (5) (ICS-S0)
The current frame is encoded 610 according to the amount of image information that has been obtained, and the process goes to step 611.
611, determine whether the current frame is the last frame in the video stream, if yes, end the video encoding, if no, go to step 601.
Before performing step 611, the following steps 612 to 614 may also be included.
And 612, calculating the image complexity ICS of all pixel points in the current frame, and summing the image complexities of all pixel points to obtain the image complexity sum of the current frame.
613, counting the times of occurrence of each value in the values of the image complexity of all the pixel points.
614, in the values of the image complexity of all the pixel points, starting from 0, performing multiplication accumulation on each value and the occurrence frequency of the value until the result of the multiplication accumulation is equal to half of sum, storing the value S of the image complexity at the moment, and updating the reference value of the current frame to be S.
Alternatively, steps 612 to 614 may be performed in parallel with steps 602 to 610 described above.
Alternatively, in the present embodiment, Q is equal to 4.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, and when the image complexity of the pixel point in the image is smaller than the threshold, the value of the image information amount of the pixel point is set to be equal to the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image as much as possible, the code rate is distributed to the image according to the image information amount of the image, and the coding quality can be improved.
In addition, according to the embodiment of the application, for the dynamic image, for the current image to be processed, the parameter value of the previous frame image is adopted to determine the threshold value, and the reference value does not need to be calculated in real time, so that the requirement on the operation speed in the dynamic image (namely video) encoding process can be met.
The result of image coding using the method of the embodiment of the present application is tested against the JPEG2000 standard, wherein the total number of images 839 is tested. The test results are shown in tables 1 and 2.
TABLE 1 test results for static images
psnr lifting amount (sheet) psnr lifting picture to total Mean lifting value (dB)
816 97.26％ 0.516
TABLE 2 test results for successive images
Scene Arch Big_horn Factory Girl Man skateboard
psnr mean improvement/dB 0.030 2.552 0.988 0.395 0.268 0.346
Wherein psnr represents a peak signal to noise ratio (peak signal to noise ratio).
arch denotes a daytime fast moving scene, bighorn denotes a scene of flickering light at night, factory denotes a daytime low-speed scene, girl denotes a scene of an indoor portrait, man denotes a scene of a portrait under strong light (e.g., sunlight), and skateboard denotes a scene of a dusk fast moving scene.
As can be seen from tables 1 and 2, there is a large degree of enhancement in psnr, whether for a static image or a continuous dynamic image.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image to a certain extent, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved.
The various embodiments described herein may be implemented as stand-alone solutions or combined in accordance with inherent logic and are intended to fall within the scope of the present application.
Embodiments of the method of the present application are described above, and embodiments of the apparatus of the present application are described below. It is to be understood that the description of the apparatus embodiments corresponds to the description of the method embodiments, and therefore reference may be made to the preceding method embodiments for parts which are not described in detail.
Fig. 7 is a schematic block diagram of an encoding apparatus 700 provided in an embodiment of the present application. The encoding apparatus 700 is used to implement the method of the above method embodiments. The encoding apparatus 700 includes an obtaining unit 710 and a determining unit 720.
The obtaining unit 710 is configured to obtain a first image, where the first image includes a first pixel.
A determining unit 720, configured to determine, when the image complexity of the first pixel is greater than a threshold, that the value of the image information amount of the first pixel is a first value, where the first value is smaller than the image complexity of the first pixel, and the threshold is less than or equal to 2P -QP is the bit depth of the first picture, Q is a positive integer less than P.
For example, Q is equal to 4 or other positive integer less than P.
For example, the bit depth of the first image is 8, 10, 12, 14, or 16, etc., i.e., P may take on a value of 8, 10, 12, 14, or 16, etc.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image to a certain extent, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved. In other words, the method and the device can determine the more appropriate image information amount, thereby realizing more reasonable code rate distribution and further improving the coding quality.
Optionally, in some embodiments, the obtaining unit 710 is further configured to obtain a reference value, where the reference value is a value of image complexity of a pixel point in the second image.
The determining unit 720 is further configured to: when the reference value is less than 2P-QWhen the threshold value is determined to be equal to the reference value;
when the reference value is greater than or equal to 2P-QWhen the threshold is determined to be equal to 2P-QAnd the second image is the first image, or the second image is a frame image before the first image.
Optionally, in some embodiments, the reference value satisfies the following condition: and aiming at the image complexity of each pixel point in the second image, multiplying and accumulating the value of each image complexity and the occurrence frequency thereof from the image complexity with the lowest value until the multiplication and accumulation result is equal to or more than k times of the image complexity of the second image, wherein the value of the image complexity subjected to multiplication and accumulation is a reference value, and k is a positive number less than 1. For example, k is equal to 0.5.
Optionally, in some embodiments, the second image is the first image, and the obtaining unit 710 is configured to: counting the occurrence frequency of the value of each image complexity according to the image complexity of each pixel point in the first image; starting from the image complexity with the lowest value in the values of the image complexities, multiplying and accumulating each value and the occurrence frequency thereof until the multiplying and accumulating result is equal to or more than k times of the image complexity of the first image; and taking the value of the image complexity subjected to multiply accumulation finally as a reference value.
Optionally, in some embodiments, when the first image is a frame of image in the video stream, the second image is a frame of image before the first image.
Optionally, in some embodiments, the image complexity of the second image is equal to the sum of the image complexities of all pixel points in the second image.
Optionally, in some embodiments, the determining unit 720 is configured to determine the value of the image information amount of the first pixel according to the threshold and the image complexity of the first pixel.
Optionally, in some embodiments, the determining unit 720 is configured to determine the value V of the image information amount of the first pixel point according to formula (2).
Optionally, in some embodiments, the determining unit 720 is further configured to determine, when the image complexity of the first pixel point is less than or equal to the threshold, that the value of the image information amount of the first pixel point is a second value, where the second value is equal to or greater than the image complexity of the first pixel point.
It is to be understood that the obtaining unit 710 and the determining unit 720 may be implemented by a processor or processor-related circuitry.
As shown in fig. 8, an encoding apparatus 800 is further provided in an embodiment of the present application, where the encoding apparatus 800 includes a processor 810 and a memory 820, where the memory 820 stores instructions or programs, and the processor 810 is configured to execute the instructions or programs stored in the memory 820. When the instructions or programs stored in the memory 820 are executed, the processor 810 is configured to perform the methods of the above-described method embodiments.
Optionally, the encoding apparatus 800 may further comprise a transceiver 830, and the processor 810 is configured to control the transceiver 830 to receive and/or transmit signals.
It is understood that the encoding apparatus 800 may correspond to the encoding apparatus 700 of the above-described embodiment.
Therefore, by setting the threshold, when the image complexity of the pixel point in the image is larger than the threshold, the value of the image information amount of the pixel point is set to be smaller than the image complexity of the pixel point, so that the image information amount of the image is close to the image information amount actually contained in the image to a certain extent, the code rate is distributed to the image according to the image information amount of the image, and the encoding quality can be improved. In other words, the method and the device can determine the more appropriate image information amount, thereby realizing more reasonable code rate distribution and further improving the coding quality.
The embodiment of the present application further provides a chip, where the chip includes a processing module and a communication interface, the processing module is configured to control the communication interface to communicate with the outside, and the processing module is further configured to implement the method in the foregoing method embodiment.
Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a computer, causes the computer to implement the method of the above method embodiments.
Embodiments of the present application also provide a computer program product containing instructions, which when executed by a computer, cause the computer to implement the method of the above method embodiments.
It should also be understood that the expressions "first" in the first image, first pixel point, first value referred to herein are merely for convenience of description and distinction, and are not intended to limit the scope of embodiments of the present invention.
In the above embodiments, all or part of the implementation may be realized by software, hardware, firmware or any other combination. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a Digital Video Disk (DVD)), or a semiconductor medium (e.g., a Solid State Disk (SSD)), among others.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components 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 units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units 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 units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (27)

1. A method of determining an amount of image information, comprising:
acquiring a first image to be processed, wherein the first image comprises first pixel points;
when the image complexity of the first pixel point is larger than a threshold value, determining that the value of the image information content of the first pixel point is a first value, wherein the first value is smaller than the image complexity of the first pixel point, and the threshold value is smaller than or equal to 2P -QP is the bit depth of the first picture, Q is a positive integer less than P.
2. The method of claim 1, further comprising:
acquiring a reference value, wherein the reference value is the value of the image complexity of one pixel point in the second image;
when the reference value is less than 2P-QDetermining that the threshold value is equal to the reference value;
when the reference value is greater than or equal to 2P-QWhen it is determined that the threshold is equal to 2P-Q，
The second image is the first image, or the second image is a previous frame image of the first image.
3. The method according to claim 2, characterized in that the reference value satisfies the condition:
and for the image complexity of each pixel point in the second image, performing multiplication and accumulation on the value of each image complexity and the occurrence frequency thereof from the image complexity with the lowest value until the multiplication and accumulation result is equal to or more than k times of the image complexity of the second image, wherein the value of the image complexity subjected to the multiplication and accumulation is the reference value, and k is a positive number less than 1.
4. The method of claim 3, wherein the second image is the first image, and wherein obtaining the reference value comprises:
counting the occurrence frequency of the value of each image complexity according to the image complexity of each pixel point in the first image;
starting from the lowest image complexity in the values of the image complexities, performing multiply-accumulate on each value and the occurrence frequency thereof until the multiply-accumulate result is equal to or more than k times of the image complexity of the first image;
and taking the value of the image complexity subjected to multiply accumulation finally as the reference value.
5. A method according to claim 2 or 3, wherein when the first image is a frame of image in a video stream, the second image is a frame of image preceding the first image.
6. The method of claim 3, wherein the image complexity of the second image is equal to the sum of the image complexity of all pixel points in the second image.
7. The method according to any one of claims 1 to 6, wherein determining that the value of the image information amount of the first pixel point is a first value comprises:
and determining the value of the image information amount of the first pixel point according to the threshold and the image complexity of the first pixel point.
8. The method of claim 7, wherein determining the value of the amount of image information for the first pixel comprises:
determining the value V of the image information amount of the first pixel point according to the following formula:
V＝a·ICS+b·Thr
wherein ICS represents the image complexity of the first pixel point, Thr represents the threshold, a and b are constants, a is a positive number less than 1, and the sum of a and b is equal to 1.
9. The method according to any one of claims 1 to 6, further comprising:
and when the image complexity of the first pixel point is smaller than or equal to the threshold value, determining that the value of the image information amount of the first pixel point is a second value, wherein the second value is equal to or larger than the image complexity of the first pixel point.
10. Method according to claim 3 or 4, characterized in that k is equal to 0.5.
11. The method of claim 8, wherein a is equal to 0.15 or 0.05.
12. The method of any one of claims 1 to 11, wherein Q is equal to 4.
13. An encoding apparatus, comprising:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a first image which comprises a first pixel point;
a determining unit, configured to determine that a value of an image information amount of the first pixel is a first value when the image complexity of the first pixel is greater than a threshold, where the first value is smaller than the image complexity of the first pixel, and the threshold is less than or equal to 2P-QP is the bit depth of the first picture, Q is a positive integer less than P.
14. The encoding device according to claim 13, wherein the obtaining unit is further configured to obtain a reference value, where the reference value is a value of image complexity of a pixel point in the second image;
the determination unit is further configured to:
when the reference value is less than 2P-QDetermining that the threshold value is equal to the reference value;
when the reference value is greater than or equal to 2P-QWhen it is determined that the threshold is equal to 2P-Q，
The second image is the first image, or the second image is a previous frame image of the first image.
15. The encoding apparatus according to claim 14, wherein the reference value satisfies the following condition:
and for the image complexity of each pixel point in the second image, performing multiplication and accumulation on the value of each image complexity and the occurrence frequency thereof from the image complexity with the lowest value until the multiplication and accumulation result is equal to or more than k times of the image complexity of the second image, wherein the value of the image complexity subjected to the multiplication and accumulation is the reference value, and k is a positive number less than 1.
16. The encoding device according to claim 15, wherein the second image is the first image, and the obtaining unit is configured to:
counting the occurrence frequency of the value of each image complexity according to the image complexity of each pixel point in the first image;
starting from the lowest image complexity in the values of the image complexities, performing multiply-accumulate on each value and the occurrence frequency thereof until the multiply-accumulate result is equal to or more than k times of the image complexity of the first image;
and taking the value of the image complexity subjected to multiply accumulation finally as the reference value.
17. The encoding apparatus according to claim 14 or 15, wherein when the first image is a frame image in a video stream, the second image is a frame image previous to the first image.
18. The encoding device according to claim 15, wherein the image complexity of the second image is equal to the sum of the image complexities of all pixel points in the second image.
19. The encoding device according to any one of claims 13 to 18, wherein the determining unit is configured to determine the value of the image information amount of the first pixel according to the threshold and the image complexity of the first pixel.
20. The encoding device according to claim 19, wherein the determining unit is configured to determine the value V of the amount of image information of the first pixel point according to the following formula:
V＝a·ICS+b·Thr
wherein ICS represents the image complexity of the first pixel point, Thr represents the threshold, a and b are constants, a is a positive number less than 1, and the sum of a and b is equal to 1.
21. The encoding device according to any one of claims 13 to 18, wherein the determining unit is further configured to determine that the value of the image information amount of the first pixel is a second value when the image complexity of the first pixel is less than or equal to the threshold, and the second value is equal to or greater than the image complexity of the first pixel.
22. The encoding device according to claim 15 or 16, wherein k is equal to 0.5.
23. The encoding device of claim 20, wherein a is equal to 0.15 or 0.05.
24. The encoding device according to any one of claims 13 to 23, wherein Q is equal to 4.
25. An encoding apparatus, comprising: a memory for storing instructions and a processor for executing the instructions stored by the memory, and execution of the instructions stored in the memory causes the processor to perform the method of any of claims 1 to 12.
26. A computer storage medium, having stored thereon a computer program which, when executed by a computer, causes the computer to perform the method of any one of claims 1 to 12.
27. A computer program product comprising instructions which, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 12.
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