WO2019127136A1

WO2019127136A1 - Bit rate control method and encoding device

Info

Publication number: WO2019127136A1
Application number: PCT/CN2017/119111
Authority: WO
Inventors: 缪泽翔; 郑萧桢
Original assignee: 深圳市大疆创新科技有限公司
Priority date: 2017-12-27
Filing date: 2017-12-27
Publication date: 2019-07-04
Also published as: CN109076212A

Abstract

Provided are an image processing method and device. The method comprises: receiving the image complexity of an image to be encoded, the image complexity being obtained by an image processor connected to an encoder; determining a preset coded bit of the image to be encoded; obtaining, according to the image complexity and the preset coded bit, a quantified parameter of the image to be encoded; and encoding, according to the quantified parameter of the image to be encoded, the image to be encoded. The method can take both the bit rate control accuracy and the computational complexity of the encoder into consideration.

Description

Rate control method and coding device

Copyright statement

The disclosure of this patent document contains material that is subject to copyright protection. This copyright is the property of the copyright holder. The copyright owner has no objection to the reproduction of the patent document or the patent disclosure in the official records and files of the Patent and Trademark Office.

Technical field

The present application relates to the field of video codec and, more particularly, to a method and an encoding apparatus for rate control.

Background technique

Visual information is one of the most important sources for humans to obtain external information, but the uncompressed raw video data collected by the camera occupies a huge storage space with a resolution of 1920×1080, a frame rate of 30 frames per second, and a duration of 10 For example, in the case of a minute video, storing the video without compression requires 104.28 Gbytes of storage space. In order to reduce the bandwidth occupied by video storage and transmission, it is necessary to encode and compress the video data.

The video coding process includes steps of prediction, transform, rate control, quantization, and entropy coding. Among them, the rate control plays a very important role in the video encoding process. Since the content and characteristics of different video sequences are different, if the same coding parameters are used for encoding, a very different output bit rate and different degrees of video distortion will be generated. To overcome this problem, rate control is proposed.

The rate control algorithm adaptively adjusts the encoding parameters according to the characteristics of different video images. In general, standards-based video encoders have great flexibility in the choice of encoding parameters, and the choice of encoding parameters can have a large impact on the code rate of the encoded video stream. The rate control algorithm may enable the encoder to select an appropriate coding parameter between a set of coding parameter sets to achieve the actual coded bits approximating the pre-assigned coded bits.

In the existing rate control algorithms in the industry, some algorithms may result in inaccurate rate control. Some algorithms may improve the computational complexity of the encoder while solving the inaccurate rate control.

Therefore, it is necessary to propose an encoding method that is compatible with the accuracy of the rate control and the computational complexity of the encoder.

Summary of the invention

The present application provides a code rate control method and apparatus, which can take into account the accuracy of the rate control and the computational complexity of the encoder in the rate control process.

In a first aspect, a method of rate control is provided, the method being applied to a video encoder, the method comprising: receiving image complexity of an image to be encoded, the image complexity being image processing connected to an encoder Obtaining a preset encoding bit of the image to be encoded; obtaining a quantization parameter of the image to be encoded according to the image complexity and the preset encoding bit; and according to the quantization parameter of the image to be encoded, The image to be encoded is encoded.

In a second aspect, an encoding apparatus is provided, the encoding apparatus comprising: a transceiver unit configured to receive an image complexity of an image to be encoded, the image complexity being acquired by an image processor connected to the encoder; And determining a preset coding bit of the image to be encoded; obtaining a quantization parameter of the image to be encoded according to the image complexity and the preset coding bit; and according to the quantization parameter of the image to be encoded, The image to be encoded is encoded.

In a third aspect, an encoding apparatus is provided, the encoding apparatus comprising a memory for storing instructions, the processor for executing the instructions stored by the memory, and instructions stored in the memory Execution of the processor causes the processor to perform the method provided by the first aspect.

In a fourth aspect, a chip is provided, the chip comprising a processing module and a communication interface, the processing module is configured to control the communication interface to communicate with an external, and the processing module is further configured to implement the method provided by the first aspect.

A fifth aspect, a computer readable storage medium having stored thereon a computer program, the computer program being executed by a computer to cause the computer to implement the method of any of the first aspect or the first aspect . Specifically, the computer may be the above-mentioned ** device.

In a sixth aspect, a computer program product comprising instructions, which when executed by a computer, causes the computer to implement the method provided by the first aspect.

In summary, in the embodiment of the present invention, when the rate control is performed, the image complexity is acquired by the image processor external to the encoder, and a large amount of calculations that may occur may be performed by an image processor (such as an ISP) other than the encoder. Therefore, the calculation amount and implementation complexity of the encoder can be reduced, and the encoding delay caused by the secondary encoding of the encoder can be avoided. In the meantime, the embodiment of the present invention can obtain the quantization parameter according to the image complexity and the preset coding bit, so that the rate control precision can be guaranteed to a certain extent. Therefore, the solution of the embodiment of the present invention can reduce the calculation amount and implementation complexity of the encoder without sacrificing the accuracy of the rate control, thereby improving the coding efficiency.

DRAWINGS

1 is a schematic flow chart of a video encoding process.

2 is a schematic block diagram of an image processing system in accordance with an embodiment of the present invention.

FIG. 3 is a schematic flowchart of a method for rate rate control according to an embodiment of the present invention.

4 is a schematic diagram of dividing an entire frame image into a plurality of image blocks in an embodiment of the present invention.

FIG. 5 is a schematic diagram of a pixel block in an embodiment of the present invention.

FIG. 6 is another schematic flowchart of a method for rate rate control according to an embodiment of the present invention.

Fig. 7 is a schematic block diagram of an encoding apparatus according to an embodiment of the present invention.

FIG. 8 is another schematic block diagram of an encoding apparatus according to an embodiment of the present invention.

Detailed ways

In order to facilitate understanding and description of the solution of the present application, the process of video encoding will be described below first with reference to FIG.

As shown in FIG. 1, the video encoding process includes steps of prediction, transform, quantization, and entropy coding. The explanation of these steps is as follows.

The purpose of the prediction is to use the prediction block information to remove redundant information of the current image block to be encoded. The prediction includes two types of intra prediction and inter prediction. Intra prediction is to obtain prediction block data using information of the current frame image. For example, intra prediction uses spatial domain information of the current encoded frame to eliminate redundant information. Inter prediction uses the information of the reference frame to obtain prediction block data. For example, inter prediction may use time domain frame information adjacent to the front and back of the current encoded frame for eliminating redundant information. The process of inter prediction includes: first, dividing an image block to be encoded into a plurality of sub image blocks; and then, for each sub image block, searching for a picture block that best matches the current sub image block as a prediction block in the reference frame; And subtracting the sub-image block from the corresponding pixel value of the prediction block to obtain a residual, and combining the obtained residuals corresponding to each sub-image block to obtain a residual of the image block to be encoded.

At the time of video encoding processing, a video frame using only the intra prediction mode is referred to as an I frame; a video frame that can be inter-predicted using a forward reference frame is referred to as a P frame; a video frame that can have a bidirectional reference frame is referred to as an B frame. frame.

The purpose of the transformation is to remove redundant information from the image block. Specifically, the transformation matrix can be used to remove the correlation of the residuals of the image blocks, i.e., remove redundant information of the image blocks in order to improve coding efficiency. The transformation of the data block in the image block usually adopts a two-dimensional transformation, that is, the residual information of the data block is respectively multiplied by a transformation matrix and its transposed matrix, and the multiplication is obtained after the multiplication.

The purpose of quantization is to obtain quantized coefficients based on the coefficient of variation. Specifically, the transform coefficients are quantized according to the quantization parameter to obtain corresponding quantized coefficients.

The purpose of entropy coding is to obtain a bit stream by entropy coding the quantized coefficients.

As shown in FIG. 1, in the encoding process, steps such as inverse quantization and inverse transform are also included. Anti-quantization refers to the process that is the opposite of the quantification process. Inverse transformation refers to the process that is the opposite of the transformation process.

After completing the image coding, the encoding end stores or transmits the encoded bit stream obtained by entropy coding, such as intra prediction mode and motion vector information, to the decoding end.

At the decoding end, after obtaining the entropy-encoded bit stream, first, entropy decoding the bit stream to obtain a corresponding residual; and then obtaining a predicted image block according to the decoded motion vector or intra-coding prediction mode information; The value of each pixel in the current sub-image block is obtained according to the residual of the predicted image block and the image block.

In the video coding process, in addition to the above steps of prediction, transformation, quantization and entropy coding, rate control also plays a very important role.

Different video sequences have different content and characteristics. If the same encoding parameters are used to encode different video sequences, a very different output bit rate and varying degrees of video distortion will result. In order to overcome this problem, it is necessary to adaptively adjust the encoding parameters according to the characteristics of different video images. This process of adjusting the encoding parameters is called rate control.

The purpose of rate control is to dynamically adjust the coding parameters to ensure that the compressed video stream can be transmitted in real time through a fixed bandwidth channel while ensuring a certain image quality, or to satisfy the stream code file after compression for a specific time. To be less than a specified size constraint.

In general, the rate control algorithm can be divided into the following two steps:

In the first step, the coded bits are pre-allocated before each coding level is encoded.

The coding hierarchy is from high to low: group of pictures (GOP) level, single video frame level and basic sub-image block level.

In this step, the full extent of the encoder buffer is also considered.

In the second step, in the encoding process of each coding level, the coding parameters are adjusted such that the actual coded bits coincide with the coded bits pre-allocated in the first step.

The coding parameters dynamically adjusted in the rate control process include: a direction mode of the intra prediction, a motion vector of the inter prediction, and a coding parameter such as a quantization parameter in the quantization process.

In the quantization process, the scaling of the transform coefficients is performed by the quantization parameters, the transform coefficients are input, and the quantized coefficients are output. The process is as follows:

Wherein, quantizedCoeff represents a quantized coefficient; transformed Coeff represents a transform coefficient; QP represents a quantization parameter; and f(QP) represents a quantization step size, which is a scalar determined by a quantization parameter QP.

Since the quantized coefficients enter the entropy coder, they are further encoded into a binary code stream, and the bit quantity of the coded quantized coefficients is very high in the code stream encoded by the entire video, and the amplitude range of the quantized coefficients is controlled by the quantization step size. The quantization step size is directly determined by the quantization parameter, so the size of the quantization parameter determines the size of the output code rate after encoding the video frame. In the case where other coding parameters are fixed, a larger quantization parameter usually causes the encoder to output a smaller code rate when encoding the same video, whereas a smaller quantization parameter causes the encoder to output a larger code rate when encoding the same video. .

Therefore, in the rate control process, one of the frequently used encoding parameters is a quantization parameter.

In the existing rate control algorithm in the industry, in order to improve the accuracy of the rate control, the feature information of some images is obtained by preprocessing for rate control before the encoder starts encoding. However, before the encoding, the encoder performs the pre-processing process, which causes the encoding delay, which affects the running speed of the encoder, which is not conducive to real-time encoding.

In view of the above problems, the present application proposes a method and an encoding apparatus for rate control, which can balance both the accuracy of the rate control and the computational complexity of the encoder.

In the present application, first, image complexity is introduced into a rate control algorithm. Secondly, image complexity information of the image to be encoded is generated by an image processor external to the encoder, such as an image signal processor (ISP).

Since the encoder is not required to perform image complexity calculations, it is possible to avoid introducing additional computational complexity and coding time-consuming for the encoder. At the same time, since the video signal is collected by the camera and then transmitted to the video encoder, it is first processed by an image processor (such as an ISP). Therefore, image complexity information generated by the image processor is not in the image processing system. Introduce additional components.

2 is a schematic structural diagram of an image processing system according to an embodiment of the present invention. The system includes an image processor 210 and an encoding device 220. The encoding device 220 includes a prediction module 221, a transform module 222, a code rate control module 223, a quantization module 224, and an entropy encoding module 225.

The image processor 210 is configured to receive a sequence of images to be encoded, calculate its image complexity, and input the image complexity into the rate control module 223.

Specifically, the image processor 210 is an ISP.

The prediction module 221 is configured to receive a sequence of images to be encoded, predict the same, and obtain a corresponding residual signal.

The change module 222 is configured to receive the residual signal output by the prediction module 221, transform it, and obtain a corresponding transform parameter.

The rate control module is configured to, 223, obtain a corresponding quantization parameter according to the preset coded bits and the image complexity acquired from the image processor 210.

The quantization module 224 is configured to receive the transformation parameters of the variation module 222 and the quantization parameters output by the rate control module 223, and quantize the variation parameters by using the quantization parameters to obtain corresponding quantization coefficients.

The entropy encoding module 225 is configured to receive the quantized coefficients output by the quantization module 224, and entropy encode the quantized coefficients to obtain an encoded bit stream.

As shown in FIG. 2, the system further includes an inverse transform module and an inverse quantization module. The function of the inverse transform module is opposite to that of the transform module. The function of the inverse quantization module is opposite to that of the quantization module.

In the embodiment of the present invention, the image complexity is calculated by an image processor external to the encoder, and the image complexity is used to perform rate control in the image encoding process. On the one hand, the accuracy of the rate control is guaranteed to a certain extent; on the other hand, a large amount of calculations that may occur are performed by an image processor external to the encoder, which can reduce the computation and implementation complexity of the encoder.

FIG. 3 is a schematic flowchart of a method for rate rate control according to an embodiment of the present invention. The method can be performed by a video encoder, such as by encoding device 220 shown in FIG. As shown in FIG. 3, the method includes the following steps.

310. Receive image complexity of an image to be encoded, the image complexity being acquired by an image processor connected to the encoder.

Specifically, the image processor acquires the image complexity of the image to be encoded, and then the encoder receives the image complexity of the image to be encoded from the image processor. The image processor is located external to the encoder. For example, the image processor is an ISP.

Specifically, the image complexity of the image to be encoded is obtained according to the texture information of the image to be encoded. It should be understood that the image complexity obtained by calculating the texture information of an image can characterize the amount of information of the image. Alternatively, the image complexity of the image to be encoded is determined according to the degree of fluctuation of the pixels in the image to be encoded, that is, the image complexity of the image to be encoded indicates the degree of fluctuation of the pixels in the region to be encoded.

320. Determine a preset coded bit of the image to be encoded.

Specifically, the preset coded bits refer to pre-assigned coded bits before image coding.

330. Obtain a quantization parameter of the image to be encoded according to the image complexity and the preset coding bit.

It should be understood that the image complexity may represent the amount of information of the image before encoding, and the preset coded bits represent the amount of information of the encoded compressed image, so it is reasonable and effective to calculate the quantization parameter by combining the image complexity and the preset encoding bit. .

340. Encode the image to be encoded according to the quantization parameter of the image to be encoded.

It should be understood that the above steps 310 to 330 belong to the rate control process. Specifically, steps 310 through 330 may be performed by a code rate control module internal to the encoder, and step 340 may be performed by an encoding module internal to the encoder (eg, a module that implements entropy encoding).

In the embodiment of the present invention, when the code rate control is performed, the image complexity is acquired by the image processor external to the encoder, and a large amount of calculations that may occur may be performed by an image processor (such as an ISP) other than the encoder, which may reduce the encoder. The computational complexity and implementation complexity can avoid the encoder's encoding delay affecting the running speed of the encoder, which in turn facilitates real-time encoding. In the meantime, the embodiment of the present invention can obtain the quantization parameter according to the image complexity and the preset coding bit, so that the rate control precision can be guaranteed to a certain extent. Therefore, the solution of the embodiment of the present invention can reduce the calculation amount and implementation complexity of the encoder without sacrificing the accuracy of the rate control, thereby improving the coding efficiency.

Optionally, in some embodiments, the image to be encoded is one image block in an image frame.

Specifically, when encoding an image of one frame, the encoder first divides the entire frame image into a plurality of 64×64 image blocks, as shown in FIG. 4, and divides one frame image into 128 image blocks, in FIG. Each block represents an image block of size 64 x 64. The encoder then encodes each image block in sequence.

Optionally, in some embodiments, the image to be encoded may also be directly a frame image.

For the convenience of description and understanding, the following is an example in which the image to be encoded is an image block in the image frame, but the embodiment of the present invention does not limit this.

Optionally, in some embodiments, the image frame in which the image to be encoded is located is an I frame.

Specifically, at the time of video encoding processing, a video frame using only the intra prediction mode is referred to as an I frame.

Since the residual signal of the I-frame image at the time of encoding is generated by intra-frame image signal prediction, it is advantageous to use the complexity information of the intra-frame image for the rate control algorithm.

Optionally, in some embodiments, the image frame in which the image to be encoded is located is a P frame.

Specifically, at the time of video encoding processing, a video frame that performs inter prediction using a forward reference frame is referred to as a P frame.

Optionally, in some embodiments, step 330 specifically includes: calculating the quantization parameter by using a first function model, where the exponential operation is not included in the first function model, and the independent variable of the first function model includes the image complexity and The preset coded bit.

Optionally, in some embodiments, the first function model only includes a logarithm operation, a multiplication operation, an addition operation, and/or a subtraction operation, and the independent variable of the first function model includes the image complexity and the preset coding bit. .

Specifically, the logarithmic operation mentioned in the embodiment of the present invention may be a logarithmic operation of various forms, for example, an e-based logarithm operation, a base 10 logarithm operation, or other values. The logarithmic operation of the base number is not limited in this embodiment of the present invention.

Optionally, in some embodiments, the coefficients in the first function model include at least one of: a first parameter for multiplication, a second parameter for multiplication, and a third for addition and/or subtraction. The parameter, the first parameter, the second parameter and the third parameter are all parameters used for rate control.

Specifically, the first parameter, the second parameter, and the third parameter are code rate control parameters owned by the code rate control module inside the encoder.

Specifically, calculating the quantization parameter of the encoded image by using the first function model includes: calculating a quantization parameter of the encoded image according to the following formula:

QP=A1·log(complexity)+A2·log(targetBits)+B (2)

Wherein QP represents the quantization parameter, complexity represents the image complexity, targetBits represents the preset coded bit, A1 represents the first parameter, A2 represents the second parameter, and B represents the third parameter, Log() represents a logarithm operation.

Optionally, in some embodiments, the absolute values of the first parameter A1 and the second parameter A2 are the same.

Optionally, in some embodiments, the image complexity of the image to be encoded is derived from texture information of the image to be encoded. In other words, an image processor (eg, an ISP) external to the encoder calculates image complexity from the texture information of the image.

Specifically, it is assumed that the image to be encoded includes M pixel blocks, the size of the pixel block is N×N, and both M and N are positive integers, and the image complexity of the image to be encoded is

SAD _j is the sum of the absolute values of the pixel differences of the jth pixel block in the M pixel blocks, and

Ave _j is the pixel average of the jth pixel block, and

Represents pixels in the jth pixel block.

As an example, a complete image (denoted as an image frame) is divided into a number of image blocks of size 64 x 64. Taking an image frame with a resolution of 1920×1080 as an example, it can be divided into 510 (30×17) image blocks. A pixel block having a size of 2 × 2 is used as a minimum unit for calculating image complexity, and a pixel block composed of four pixels x0, x1, x2, and x3 as shown in FIG. It should be understood that 1024 pixel blocks are included in one image block.

First, calculate the pixel average of the pixel block average _2×2 according to the following formula:

Average _2×2 =(x0+x1+x2+x3)/4 (3)

Next, the sum of the absolute values of the pixel differences of the pixel block is calculated according to the following formula: SAD _{2 × 2} :

Where xi represents the pixel value of the ith pixel in the pixel block.

Then, calculate the image complexity of an image block according to the following formula: Complexity _64×64 :

Wherein, SAD _2x2i represents the sum of the absolute values of the pixel differences of the i-th pixel block in the image block.

In other words, the image complexity of the image block is obtained _by adding the sum of the absolute values of the pixel differences of all the pixel blocks in the same image block, SAD _{2 × 2} .

The image complexity of an image frame can be obtained by adding the image complexity of all image blocks within the image frame.

The image complexity of an image block can be referred to as block level image complexity. The image complexity of an image frame can be referred to as frame level image complexity.

It should be understood that the above description in connection with FIG. 5 is merely an example and not a limitation. In practical applications, the minimum unit for calculating image complexity can be determined on a case-by-case basis.

Alternatively, in some embodiments, the image complexity of the image to be encoded represents the degree of volatility of pixels in the region of the image to be encoded.

As an alternative implementation, the image complexity of the image to be encoded is obtained by a frequency domain calculation method.

For example, the image processor determines the image complexity of the image to be encoded by counting the discrete (positive) cosine transform of the image to be encoded or the transform coefficients of the Hadamard transform.

As another alternative implementation, the image complexity of the image to be encoded is obtained by a pixel domain calculation method.

For example, the image processor determines the image complexity of the image to be encoded by calculating the variance or standard deviation of the pixels within the image to be encoded.

Optionally, in some embodiments, the image to be encoded is one image block in the image frame, and the step 320 specifically includes: preset the encoding bit according to the frame level, the frame level image complexity, and the image complexity of the image to be encoded, Determining a preset encoding bit of the image to be encoded, wherein the frame level preset encoding bit represents a preset encoding bit of the image frame, and the frame level image complexity refers to a sum of image complexity of all image blocks in the image frame. .

Specifically, it is assumed that the image to be encoded is the i-th image block in the image frame, and the preset encoding bit targetBits _{i of the} image to be encoded is calculated according to the following formula:

Wherein, the preset stage TargetBits represents a frame encoded bits, the complexity of the image Complexity image _i represents the i-th frame image block (i.e., the image to be encoded) is, Σ _{_j} complexity _j denotes the frame complexity level image, i.e. image frame The sum of the images of all image blocks is complex.

Specifically, for the process of calculating image complexity, please refer to the description in conjunction with FIG. 5, and details are not described herein again.

Specifically, the image frame in this embodiment is an I frame.

Alternatively, preset coded bits may be assigned to each image block in the image frame in advance before encoding begins.

Optionally, in some embodiments, the image to be encoded is an image block in an image frame, and the image frame is a P frame, and the step 320 specifically includes: a product of a frame-level preset bit and the first coefficient according to the P frame. Determining a preset bit of the image to be encoded, wherein the first coefficient is determined according to at least one of: an overall image complexity of the P frame, a sum of weights of all image blocks in the P frame, the image to be encoded Image complexity, weight of the image to be encoded, and frame level preset bits of the P frame, wherein the weight is determined by a code rate control parameter of the P frame.

Specifically, the first coefficient is a product of a ratio of an image complexity of the image to be encoded to a total image complexity of the P frame and a second coefficient, and a weight of the image to be encoded accounts for all image blocks in the P frame. The ratio of the sum of the weights is determined by the sum of the products of the third coefficients, wherein the second coefficient and the third coefficient are both greater than 0, and the sum of the second coefficient and the third coefficient is equal to one.

As an example, assuming that the image to be encoded is the i-th image block in the image frame, the preset encoding bit targetBits _{i of the} image to be encoded is calculated according to the following formula:

Wherein, targetBits represents a frame-level preset encoding bit; complexity _i represents an image complexity of an i-th image block (ie, the image to be encoded) in the image frame; ∑ _j complexity _j represents a frame-level image complexity, that is, the image The sum of the image complexity of all image blocks in the frame; weight _i represents the weight of the i-th image block (ie, the image to be encoded) in the image frame, and ∑ _j weight _j represents the sum of the weights of all image blocks in the image frame; C1 represents the second coefficient and C2 represents the third coefficient. For example, the second coefficient C1 is 1/4 and the third coefficient C2 is 3/4. In this example, the weight of the image block is the weight determined according to the code rate control parameter of the P frame.

It can be seen from the formula (6) and the formula (7) that, in the solution provided by the present application, the method of determining the preset coded bits is different for the I frame and the P frame. In other words, the rate control strategy used in the I frame encoding is different from the rate control strategy used in the P frame encoding, which is advantageous for improving the accuracy of the rate control for the following reasons.

Since the I frame does not depend on the reference information of the time domain to generate the prediction residual, the residual information obtained when the I frame is encoded represents the difference between a certain coded subblock and its spatially adjacent image. The residual information obtained when encoding the P frame more indicates the difference between the current encoded frame and the reference frame in the time domain. In other words, the residual information obtained at the time of I frame coding and P frame coding is different, and correspondingly, the code rate control strategy for the I frame and the P frame should be different in the case of rate control. In some existing rate control algorithms in the industry, the same rate control strategy as the P frame is used in the I frame coding, which leads to inaccurate rate control, which affects the quality of the encoded video.

Therefore, the present application can improve the rate control accuracy by processing the I frame coding and the P frame coding by using different rate control strategies.

Optionally, in some embodiments, the image to be encoded is an image block in an image frame in which the image to be encoded is located, and the method further includes: according to a frame level image complexity and a frame level preset of the image frame. Encoding bits to obtain quantization parameters for the image frame. The step 340 specifically includes: determining, according to the size relationship between the quantization parameter of the image to be encoded and the quantization parameter of the image frame, a quantization parameter used to encode the image to be encoded, and then using the finally determined quantization parameter to the image to be encoded. Encode.

Optionally, in some embodiments, the quantization parameter of the image to be encoded is within a range of the quantization parameter of the image frame, and the step 340 specifically includes: encoding the image to be encoded according to the quantization parameter of the image to be encoded. .

Optionally, in some embodiments, the quantization parameter of the image to be encoded is not in the range of the quantization parameter of the image frame, and the step 340 specifically includes: cutting the quantization parameter of the image to be encoded to the quantization parameter of the image frame. The image to be encoded is encoded according to the quantization parameter of the image to be encoded after the cropping.

Optionally, in some embodiments, the image to be encoded represents an image block in an entire frame of image. In other words, the encoding of the entire frame image is performed with the image block as the minimum coding unit.

Specifically, the entire frame image is first divided into a plurality of image blocks, and then each image block is sequentially encoded in steps 310 to 340 in sequence, and when the encoding of all image blocks in the image frame is completed, the entire frame image is completed. coding.

Optionally, in some embodiments, after the encoding of the image frame where the image to be encoded is completed, the method further includes: updating the first according to the frame-level actual coding bit and the frame-level preset coding bit of the image frame. The three parameters, the frame-level actual coded bits represent actual coded bits of the image frame, and the frame-level preset coded bits represent frame-level preset coded bits of the image frame.

Specifically, according to the second function model, the updated third parameter is obtained, where the argument of the second function model includes the frame-level actual coded bit, the frame-level preset coded bit, and the third parameter before the update, The second function model includes at least one of the following operations: a logarithmic operation, a multiplication operation, an addition, and/or a subtraction operation.

As an example, the updated third parameter B _new is obtained according to the following formula:

B _new =B _old +k·A1·(log(actualBits)-log(targetBits)) (8)

Wherein, the third parameter before the update is indicated, that is, the third parameter adopted by the image frame of the last completed encoding; represents the first parameter; k represents the update rate, for example, may be taken as the empirical value 2; and actualBits represents the actual coded bit at the frame level. ; targetBits represents frame-level preset encoding bits.

It should be understood that the code rate control parameter A1 (ie, the first parameter) and the code rate control parameter B (ie, the third parameter) are parameters of the encoder internal code rate control module, so that the code rate control module is more suitable for different video images. In the encoding process, after encoding one frame of image, the code rate control parameter B adaptively iteratively updates according to the difference between the frame-level actual coded bits and the frame-level preset coded bits.

In this embodiment, after the encoding of one frame of image is completed, the code rate control parameter is iteratively updated, so that the code rate control module in the encoder can be more adapted to the characteristics of different video images, thereby improving the accuracy of the rate control.

It should be understood that the various formulas described herein are merely exemplary and not limiting. For example, the parameters or coefficients in the formula can be determined based on actual needs.

FIG. 6 is another schematic flowchart of an image encoding method according to an embodiment of the present invention, which is performed by an encoder. In the description of the embodiment, the image complexity, the preset coding bits, the actual coding bits, and the quantization parameters of the image block are respectively recorded as: block-level image complexity, block-level preset coding bits, block-level actual coding bits, Block level quantization parameters. The image complexity, preset coding bits, actual coding bits, and quantization parameters of the entire frame image are respectively recorded as: frame-level image complexity, frame-level preset coding bits, frame-level actual coding bits, and frame-level quantization parameters. As shown in FIG. 6, the method includes the following steps.

6001, obtaining block level image complexity from an image processor that is external to the encoder.

6002. Determine block level preset coding bits.

6003, the block-level image complexity determined according to step 6001 and the block-level preset coding bit determined in step 6002, and combined with the code rate control parameter (such as the first parameter, the second parameter, and the third parameter in the foregoing embodiment), Calculate block level quantization parameters.

6004, obtaining frame level image complexity from the image processor.

6005, determining frame level preset coding bits.

6006, according to the frame-level image complexity determined in step 6004 and the frame-level preset coding bits determined in step 6005, and combined with the code rate control parameters (such as the first parameter, the second parameter, and the third parameter in the foregoing embodiments), Calculate frame level quantization parameters.

6007. Determine whether the block-level quantization parameter obtained in step 6003 is within the range of the frame-level quantization parameter obtained in step 6006. If yes, go to step 6008, and if no, go to step 6009.

6008. The block-level quantization parameter obtained in step 6003 is clipped to a certain range of the frame-level quantization parameter obtained in step 6006, and the process proceeds to step 6009.

6009. Input the block-level quantization parameter finally obtained into the quantization module to perform coding of the image block.

Specifically, if the determination result of step 6007 is YES, the block-level quantization parameter obtained in step 6003 is input into the quantization module; if the determination result in step 6007 is negative, the block-level quantization parameter after the clipping in step 6008 is input. Quantization module.

6010. Determine whether the encoding of the current one frame complete image is completed. If yes, go to step 6011, and if no, go to step 6012.

6011: Update the code rate control parameter used in step 6006 according to the frame-level actual coding bit and the frame-level preset coding bit of the currently completed encoded image frame. Go to step 6006.

Specifically, the third parameter as described in the foregoing embodiment is updated. For details, refer to the related description above, and details are not described herein again.

6012. Allocate block-level preset coding bits for the next image block to be encoded according to the block-level actual coding bits and the block-level preset coding bits of the currently completed coded image block. Go to step 6002.

Specifically, after the encoding of one image block is completed, the preset coded bits may be allocated to the next image block to be encoded according to the difference between the actual coded bits of the image block and the preset coded bits.

It should be understood that by setting the frame-level quantization parameter and the block-level quantization parameter, the image quality within one frame can be stabilized while ensuring the accuracy of the code rate control.

It should also be understood that there is no strict order relationship between step 6001, step 6002, step 6004, and step 6005 in the above process.

The method embodiments of the present application have been described above, and the device embodiments of the present application will be described below. It should be understood that the description of the device embodiments and the description of the method embodiments correspond to each other. Therefore, for the details that are not described in detail, reference may be made to the foregoing method embodiments, and for brevity, no further details are provided herein.

FIG. 7 is a schematic block diagram of an encoding apparatus 700 according to an embodiment of the present invention. The encoding apparatus 700 includes:

The transceiver unit 710 is configured to receive image complexity of the image to be encoded, where the image complexity is acquired by an image processor connected to the encoder;

The processing unit 720 is configured to determine a preset encoding bit of the image to be encoded, obtain a quantization parameter of the image to be encoded according to the image complexity and the preset encoding bit, and obtain the quantization parameter according to the quantization parameter of the image to be encoded. The encoded image is encoded.

Optionally, in some embodiments, the processing unit 720 is specifically configured to calculate the quantization parameter by using a first function model, where the first function model only includes a logarithm operation, a multiplication operation, an addition, and/or a subtraction operation, where The argument of the first function model includes the image complexity and the preset coded bits.

Optionally, in some embodiments, the first function model is: a product of a logarithm operation value of the image complexity and the first parameter, a logarithm operation value of the preset coded bit, and a third parameter The sum of the product and the second parameter.

Optionally, in some embodiments, the absolute values of the first parameter and the second parameter are the same.

Optionally, in some embodiments, after the encoding of the image frame in which the image to be encoded is completed, the processing unit 720 is further configured to: according to the frame-level actual encoding bit and the frame-level preset encoding bit of the image frame, Updating the third parameter, the frame-level actual coded bits represent actual coded bits of the image frame, the frame-level preset coded bits representing frame-level preset coded bits of the image frame.

Optionally, in some embodiments, the processing unit 720 is specifically configured to obtain, according to the second function model, an updated third parameter, where the argument of the second function model includes the frame-level actual coded bit, the frame The level preset coded bits, and the third parameter before the update, the second function model includes at least one of the following operations: a logarithmic operation, a multiplication operation, an addition, and/or a subtraction operation.

Optionally, in some embodiments, the second function model is: a difference between a logarithm operation value of the frame-level actual coded bit and a logarithm operation value of the frame-level preset coded bit, and an update rate value and the first The product of a parameter, the sum of the third parameter before the update.

Optionally, in some embodiments, the image to be encoded is an image block in an image frame in which the image to be encoded is located; the processing unit 720 is specifically configured to: preset a coding bit according to a frame level of the image frame, The frame-level image complexity of the image frame and the image complexity of the image to be encoded determine a preset encoded bit of the image to be encoded.

Optionally, in some embodiments, the processing unit 720 is configured to: according to a ratio of image complexity of the image to be encoded to a frame-level image complexity of the image frame, and a frame-level preset encoding of the image frame. The product of the bits determines the preset coded bits of the image to be encoded.

Optionally, in some embodiments, the image to be encoded is one image block in an image frame in which the image to be encoded is located; the processing unit 720 is further configured to preset according to image complexity and frame level of the image frame. Encoding a bit, obtaining a quantization parameter of the image frame; when encoding the image to be encoded, the processing unit 720 is specifically configured to: when the quantization parameter of the image to be encoded is within a range of the quantization parameter of the image frame, according to The quantization parameter of the image to be encoded is encoded by the image to be encoded.

Optionally, in some embodiments, when the image to be encoded is encoded, the processing unit 720 is specifically configured to: when the quantization parameter of the image to be encoded is not within the range of the quantization parameter of the image frame, The quantization parameter of the image to be encoded is clipped to the range of the quantization parameter of the image frame, and the image to be encoded is encoded according to the quantization parameter of the image to be encoded after the clipping.

Optionally, in some embodiments, the image frame in which the image to be encoded is located is a P frame, and the image to be encoded is an image block in the P frame; the processing unit 720 is specifically configured to: according to the frame of the P frame The product of the preset bits and the first coefficient determines a preset bit of the image to be encoded, wherein the first coefficient is determined according to at least one of: an overall image complexity of the P frame, all images in the P frame The sum of the weights of the blocks, the image complexity of the image to be encoded, the weight of the image to be encoded, and the frame level preset bits of the P frame, wherein the weight is determined by the code rate control parameter of the P frame.

Optionally, in some embodiments, the processing unit 720 is specifically configured to: the first coefficient is a product of a ratio of an image complexity of the image to be encoded to a total image complexity of the P frame and a second coefficient, Determining, by the sum of the ratio of the weight of the image to be encoded to the sum of the weights of all image blocks in the P frame and the product of the third coefficient, wherein the second coefficient and the third coefficient are both greater than 0, and the second The sum of the coefficient and the third coefficient is equal to one.

Optionally, in some embodiments, the image complexity of the image to be encoded is obtained according to texture information of the image to be encoded.

Optionally, in some embodiments, the image complexity of the image to be encoded indicates the degree of fluctuation of the pixels in the area of the image to be encoded.

Optionally, in some embodiments, the image complexity of the image to be encoded is obtained by counting the discrete positive/cosine transform of the image to be encoded or the transform coefficient of the Hadamard transform.

Optionally, in some embodiments, the image complexity of the image to be encoded is obtained by calculating a variance or a standard deviation of pixels within the image to be encoded.

Optionally, in some embodiments, the image processor is an image signal processor ISP.

The processing unit 710 in this embodiment specifically includes: a code rate control unit, a prediction unit, a transform unit, an inverse transform unit, a quantization unit, an inverse quantization unit, and an entropy coding unit. The code rate control unit is configured to implement rate control and provide quantization parameters for the quantization unit. Specifically, the code rate control unit is configured to receive image complexity from the image processor, and then calculate the quantization parameter according to the image complexity and the preset coded bits.

As shown in FIG. 8, an embodiment of the present invention further provides an encoding apparatus 800, a processor 810 and a memory 820. The memory 820 is configured to store an instruction, and the processor 810 is configured to execute an instruction stored by the memory 820, and Execution of the instructions stored in memory 820 is such that processor 810 is operative to perform the methods of the above method embodiments.

Specifically, the encoding device 800 further includes a transceiver 830 for receiving image complexity information from an external image processor (eg, an ISP).

Embodiments of the present invention also provide a computer storage medium having stored thereon a computer program that, when executed by a computer, causes the computer to perform the method of the above method embodiments.

Embodiments of the present invention also provide a computer program product comprising instructions, wherein the instructions, when executed by a computer, cause a computer to perform the method of the above method embodiments.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented in software, it 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 the computer program instructions are loaded and executed on a computer, the processes or functions described in accordance with embodiments of the present invention are generated in whole or in part. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be from a website site, computer, server or data center Transmission to another website site, computer, server or data center via wired (eg coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (eg infrared, wireless, microwave, etc.). The computer readable storage medium can be any available media that can be accessed by a computer or a data storage device such as a server, data center, or the like that includes one or more available media. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a digital video disc (DVD)), or a semiconductor medium (such as a solid state disk (SSD)). .

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the solution. A person skilled in the art can use different methods to implement the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present application.

In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the coding device embodiment described above is only illustrative. For example, the division of the unit is only a logical function division, and the actual implementation may have another division manner, for example, multiple units or components may be combined. Or it can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

The foregoing is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto, and any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application. It should be covered by the scope of protection of this application. Therefore, the scope of protection of the present application should be determined by the scope of the claims.

Claims

A method of rate control, characterized in that the method is applied to a video encoder, the method comprising:

Receiving image complexity of the image to be encoded, the image complexity being acquired by an image processor connected to the encoder;

Determining a preset encoding bit of the image to be encoded;

Obtaining a quantization parameter of the image to be encoded according to the image complexity and the preset coding bit;

And encoding the image to be encoded according to the quantization parameter of the image to be encoded.
The method according to claim 1, wherein the obtaining the quantization parameter of the image to be encoded according to the image complexity and the preset coding bit comprises:

Calculating the quantization parameter using a first function model, the first function model only including a logarithm operation, a multiplication operation, an addition operation, and/or a subtraction operation, the independent variable of the first function model including the image complexity and the Preset coded bits.
The method of claim 2 wherein the coefficients in the first function model comprise at least one of: a first parameter for multiplication, a second parameter for multiplication, and addition and/or subtraction. The third parameter of the operation, the first parameter, the second parameter and the third parameter are all parameters for rate control.
The method according to claim 3, wherein the first function model comprises: a product of a logarithm operation value of the image complexity and the first parameter, and a logarithm operation of the preset coded bit The sum of the value and the third parameter, and the sum of the second parameter.
The method according to claim 3 or 4, wherein the absolute values of the first parameter and the second parameter are the same.
The method according to any one of claims 3 to 5, wherein after the encoding of the image frame in which the image to be encoded is to be completed, the method further comprises:

Updating the third parameter according to a frame-level actual coded bit of the image frame and a frame-level preset coded bit, where the frame-level actual coded bit represents an actual coded bit of the image frame, the frame-level preset code The bits represent the frame level preset coded bits of the image frame.
The method according to claim 6, wherein the updating the third parameter according to the frame-level actual coding bit and the frame-level preset coding bit of the image frame comprises:

Obtaining, according to the second function model, an updated third parameter, where the argument of the second function model includes the frame-level actual coded bit, the frame-level preset coded bit, and a third parameter before updating, The second function model includes at least one of the following operations: a logarithmic operation, a multiplication operation, an addition, and/or a subtraction operation.
The method according to claim 7, wherein the second function model comprises: a difference between a logarithmic operation value of the frame-level actual coded bit and a logarithm operation value of the frame-level preset coded bit The sum of the rate value and the first parameter, and the third parameter before the update.
The method according to any one of claims 1 to 5, wherein the image to be encoded is one image block in an image frame in which the image to be encoded is located;

Determining the preset coded bits of the image to be encoded, including:

Determining, according to a frame-level preset encoding bit of the image frame, a frame-level image complexity of the image frame, and an image complexity of the image to be encoded, determining a preset encoding bit of the image to be encoded.
The method according to claim 9, wherein the determining the preset encoding bit of the image to be encoded comprises:

Determining, according to a ratio of image complexity of the image to be encoded to a frame-level image complexity of the image frame, a product of a frame-level preset encoding bit of the image frame, determining a preset encoding bit of the image to be encoded. .
The method according to any one of claims 1 to 5, 9 or 10, wherein the image to be encoded is one image block in an image frame in which the image to be encoded is located;

The method further includes:

Obtaining a quantization parameter of the image frame according to an image complexity of the image frame and a frame-level preset encoding bit;

And encoding, according to the quantization parameter of the image to be encoded, the image to be encoded, including:

When the quantization parameter of the image to be encoded is within the range of the quantization parameter of the image frame, the image to be encoded is encoded according to the quantization parameter of the image to be encoded.
The method according to claim 11, wherein the encoding the image to be encoded according to the quantization parameter of the image to be encoded further comprises:

When the quantization parameter of the image to be encoded is not within the range of the quantization parameter of the image frame, trimming the quantization parameter of the image to be encoded into a range of quantization parameters of the image frame, according to the clipping The quantization parameter of the image to be encoded encodes the image to be encoded.
The method according to any one of claims 1 to 12, wherein the image frame in which the image to be encoded is located is an I frame.
The method according to claim 1, wherein the image frame in which the image to be encoded is located is a P frame, and the image to be encoded is one image block in the P frame;

Determining the preset coded bits of the image to be encoded, including:

Determining a preset bit of the image to be encoded according to a product of a frame level preset bit of the P frame and a first coefficient, wherein the first coefficient is determined according to at least one of: a totality of the P frame Image complexity, sum of weights of all image blocks in the P frame, image complexity of the image to be encoded, weight of the image to be encoded, and frame level preset bits of the P frame, wherein The weight is determined by the rate control parameter of the P frame.
The method according to claim 14, wherein the first coefficient is a product of a ratio of an image complexity of the image to be encoded to an overall image complexity of the P frame and a second coefficient, Determining, by the sum of the ratio of the weight of the encoded image to the sum of the weights of all the image blocks in the P frame and the product of the third coefficient, wherein the second coefficient and the third coefficient are both greater than 0, and The sum of the second coefficient and the third coefficient is equal to one.
The method according to any one of claims 1 to 15, wherein the image complexity of the image to be encoded is obtained based on texture information of the image to be encoded.
The method according to any one of claims 1 to 15, wherein the image complexity of the image to be encoded represents the degree of fluctuation of the pixels in the area of the image to be encoded.
The method according to claim 17, wherein the image complexity of the image to be encoded is obtained by counting the discrete positive/cosine transform of the image to be encoded or the transform coefficient of the Hadamard transform.
The method according to claim 17, wherein the image complexity of the image to be encoded is obtained by calculating a variance or a standard deviation of pixels within the image to be encoded.
The method according to any one of claims 1 to 19, wherein the image processor is an image signal processor ISP.
An encoding device, comprising:

a transceiver unit, configured to receive image complexity of an image to be encoded, the image complexity being acquired by an image processor connected to the encoder;

a processing unit, configured to determine a preset encoding bit of the image to be encoded; obtain a quantization parameter of the image to be encoded according to the image complexity and the preset encoding bit; and perform quantization parameter according to the image to be encoded Encoding the image to be encoded.
The encoding apparatus according to claim 21, wherein the processing unit is specifically configured to calculate the quantization parameter by using a first function model, the first function model only including a logarithm operation, a multiplication operation, an addition, and / or subtraction, the argument of the first function model includes the image complexity and the preset coded bits.
The encoding apparatus according to claim 22, wherein the coefficients in said first function model comprise at least one of: a first parameter for multiplication, a second parameter for multiplication, and addition and/or a third parameter of the subtraction operation, wherein the first parameter, the second parameter, and the third parameter are parameters for rate control.
The encoding apparatus according to claim 23, wherein said first function model comprises: a product of a logarithmically operated value of said image complexity and said first parameter, and a logarithm of said preset encoded bit The sum of the calculated value and the third parameter, and the sum of the second parameter.
The encoding device according to claim 23 or 24, characterized in that the absolute values of the first parameter and the second parameter are the same.
The encoding apparatus according to any one of claims 22 to 25, wherein after the encoding of the image frame in which the image to be encoded is to be completed, the processing unit is further configured to:

Updating the third parameter according to a frame-level actual coded bit of the image frame and a frame-level preset coded bit, where the frame-level actual coded bit represents an actual coded bit of the image frame, the frame-level preset code The bits represent the frame level preset coded bits of the image frame.
The encoding apparatus according to claim 26, wherein the processing unit is configured to obtain an updated third parameter according to a second function model, wherein an argument of the second function model includes the frame level The actual coded bits, the frame-level preset coded bits, and the third parameter before the update, the second function model includes at least one of the following operations: a logarithmic operation, a multiplication operation, an addition, and/or a subtraction operation.
The encoding apparatus according to claim 27, wherein said second function model comprises: a difference between a logarithmic operation value of said frame-level actual coded bits and a logarithm operation value of said frame-level preset coded bits The sum of the product of the update rate value and the first parameter, and the third parameter before the update.
The encoding device according to any one of claims 21 to 25, wherein the image to be encoded is one image block in an image frame in which the image to be encoded is located;

The processing unit is configured to determine, according to a frame-level preset encoding bit of the image frame, a frame-level image complexity of the image frame, and an image complexity of the image to be encoded, Set the coded bits.
The encoding apparatus according to claim 29, wherein the processing unit is configured to: according to a ratio of image complexity of the image to be encoded to a frame-level image complexity of the image frame, and the image A product of frame-level preset coded bits of the frame determines a preset coded bit of the image to be encoded.
The encoding device according to any one of claims 21 to 25, 29 or 30, wherein the image to be encoded is one image block in an image frame in which the image to be encoded is located;

The processing unit is further configured to acquire, according to an image complexity of the image frame and a frame-level preset encoding bit, a quantization parameter of the image frame;

When the image to be encoded is encoded, the processing unit is specifically configured to: when the quantization parameter of the image to be encoded is within a range of the quantization parameter of the image frame, according to the quantization parameter of the image to be encoded Encoding the image to be encoded.
The encoding apparatus according to claim 31, wherein, when encoding the image to be encoded, the processing unit is specifically configured to: when a quantization parameter of the image to be encoded is not a quantization parameter of the image frame The quantization parameter of the image to be encoded is clipped to the range of the quantization parameter of the image frame, and the image to be encoded is encoded according to the quantization parameter of the image to be encoded after the clipping.
The encoding device according to any one of claims 21 to 32, wherein the image frame in which the image to be encoded is located is an I frame.
The encoding device according to claim 21, wherein the image frame in which the image to be encoded is located is a P frame, and the image to be encoded is one image block in the P frame;

The processing unit is configured to determine, according to a product of a frame-level preset bit of the P frame and a first coefficient, a preset bit of the image to be encoded, where the first coefficient is determined according to at least one of the following: The overall image complexity of the P frame, the sum of the weights of all image blocks in the P frame, the image complexity of the image to be encoded, the weight of the image to be encoded, and the frame level of the P frame. a preset bit, wherein the weight is determined by a code rate control parameter of the P frame.
The encoding apparatus according to claim 34, wherein the first coefficient is a product of a ratio of an image complexity of the image to be encoded to an overall image complexity of the P frame and a second coefficient, and Determining, by the sum of the weight of the image to be encoded, the sum of the weights of all the image blocks in the P frame and the product of the third coefficient, wherein the second coefficient and the third coefficient are both greater than 0, And the sum of the second coefficient and the third coefficient is equal to one.
The encoding apparatus according to any one of claims 21 to 35, wherein the image complexity of the image to be encoded is obtained based on texture information of the image to be encoded.
The encoding apparatus according to any one of claims 21 to 36, characterized in that the image complexity of the image to be encoded represents the degree of fluctuation of the pixels of the area in the image to be encoded.
The encoding apparatus according to claim 37, wherein the image complexity of the image to be encoded is obtained by counting the discrete positive/cosine transform of the image to be encoded or the transform coefficient of the Hadamard transform.
The encoding apparatus according to claim 37, wherein the image complexity of the image to be encoded is obtained by calculating a variance or a standard deviation of pixels within the image to be encoded.
The encoding device according to any one of claims 21 to 39, wherein the image processor is an image signal processor ISP.
An encoding apparatus, comprising: a memory for storing instructions, said processor for executing instructions stored in said memory, and performing execution of instructions stored in said memory such that The processor is operative to perform the method of any one of claims 1 to 20.
A computer storage medium, characterized in that a computer program is stored thereon, the computer program being executed by a computer such that the computer performs the method of any one of claims 1 to 20.
A computer program product comprising instructions, wherein the instructions, when executed by a computer, cause a computer to perform the method of any one of claims 1 to 20.