CN-116258782-B - Image compression method, image encoding method, image decoding method and device

CN116258782BCN 116258782 BCN116258782 BCN 116258782BCN-116258782-B

Abstract

The application discloses an image compression method, an image encoding method, an image decoding method and an image decoding device. The image compression method comprises the steps of carrying out convolution processing on image features to be processed based on a multiscale receptive field to obtain multiple context features of the image features to be processed, determining the image features to be processed based on the image features of the image to be compressed, fusing the multiple context features to obtain sample features of the image features to be processed, and obtaining a compression result of the image to be compressed based on the sample features of the image features to be processed. The application can effectively utilize the neighborhood information in various ranges and can effectively eliminate the encoding/decoding redundancy.

Inventors

ZHAN CHUNMEI
DAI LIANG
JIANG DONG
LIN JUCAI
JIN HENG
YIN JUN

Assignees

浙江大华技术股份有限公司

Dates

Publication Date: 20260508
Application Date: 20230207

Claims (12)

1. A method of end-to-end image compression, the method comprising: carrying out convolution processing on the image characteristics to be processed based on the multiscale receptive field to obtain multiple context characteristics of the image characteristics to be processed; fusing the multiple context features to obtain sample features of the image features to be processed; Obtaining a compression result of the image to be compressed based on the sample characteristics of the image characteristics to be processed; The method comprises the steps of carrying out convolution processing on the image features to be processed by utilizing at least one convolution kernel and at least two masks to obtain multiple context features, wherein the effective areas of the at least two masks corresponding to each convolution kernel are different, and the effective areas of the masks are areas which are not 0 in the masks.
2. The image compression method according to claim 1, wherein the convolution processing is performed on the image feature to be processed based on the multiscale receptive field to obtain multiple context features of the image feature to be processed, including: And carrying out convolution processing on the image characteristics to be processed by utilizing convolution cores corresponding to the receptive fields of all scales to obtain various context characteristics, wherein: The sizes of the convolution kernels corresponding to the receptive fields of different scales are different.
3. The image compression method according to claim 1, wherein the compression direction of the image is from a first direction to a second direction, from a third direction to a fourth direction; Points in the mask where the value is not 0 are located in the third direction and in the positive first direction of the center point of the mask.
4. The image compression method of claim 1, wherein the fusing the plurality of contextual features comprises: and carrying out convolution fusion on the multiple context features to obtain sample features of the image features to be processed.
5. The image compression method according to claim 1, wherein the convolution processing is performed on the image feature to be processed based on the multiscale receptive field to obtain multiple context features of the image feature to be processed, including: Based on the receptive field of multiple scales, carrying out convolution processing on the image feature to be processed in each sub-feature to obtain multiple context features of the image feature to be processed in each sub-feature; The fusing of the multiple contextual features to obtain sample features of the image features to be processed comprises the steps of fusing the multiple contextual features of the image features to be processed of each sub-feature to obtain sample features of the image features to be processed of each sub-feature; The method comprises the steps of obtaining a compression result of an image to be compressed based on sample characteristics of the image characteristics to be processed of each sub-characteristic.
6. The method according to claim 5, wherein the dividing the image feature of the image to be compressed into a plurality of sub-features by channels includes dividing the image feature of the image to be compressed into the plurality of sub-features by channels based on an inter-channel information distribution among the image features of the image to be compressed.
7. A method of end-to-end image coding, the method comprising: Obtaining image characteristics to be processed based on the image characteristics of the image to be compressed; Processing the image characteristics to be processed by the image compression method according to any one of claims 1 to 6 to obtain a compression result of the image to be compressed; And obtaining the coding code stream of the image to be compressed based on the compression result.
8. A method of end-to-end image decoding, the method comprising: Decoding a code stream of an image to be compressed to obtain image characteristics of the image to be compressed; processing image features to be processed in the image features of the image to be compressed by the image compression method of claim 1 to obtain a compression result of the image to be compressed; and obtaining a decoded image of the code stream based on the compression result.
9. The image decoding method according to claim 8, wherein the processing the image feature to be processed in the image feature of the image to be compressed by the image compression method according to claim 1, to obtain the compression result of the image to be compressed, includes: The method comprises the steps of carrying out convolution processing on image features to be processed based on multiscale receptive fields to obtain a plurality of intermediate features of an image to be compressed, wherein data of the image features to be processed in the intermediate features corresponding to each receptive field are context features corresponding to each receptive field, and the data of the processed image features in the intermediate features are equivalent to the data in the image features of the image to be compressed; fusing the plurality of intermediate features to obtain updated features of the image to be compressed; If the image feature to be processed is not the last feature in the image features of the image to be compressed, taking the updated feature of the image to be compressed as the image feature of the image to be compressed and taking the next feature of the image feature to be processed as the image feature to be processed; And returning to the step of executing the multiscale-based receptive field, and carrying out convolution processing on the image features to be processed to obtain a plurality of intermediate features of the image to be compressed until the image features to be processed are the last features in the image features of the image to be compressed, so as to obtain the compression result.
10. An encoder comprising a processor for executing instructions to carry out the steps of the method of claim 7.
11. A decoder comprising a processor for executing instructions to implement the steps of the method as claimed in claim 8 or 9.
12. A computer readable storage medium having stored thereon instruction/program data, wherein the instruction/program data when executed implement the steps of the method of any of claims 1-6 or 7 or 8-9.

Description

Image compression method, image encoding method, image decoding method and device Technical Field The present application relates to the field of image encoding and decoding technologies, and in particular, to an end-to-end image compression method, an image encoding method, an image decoding method, and an apparatus. Background The image encoding method and the image decoding method may include a context processing step of determining a sample feature of the image feature to be processed based on context information of the image feature to be processed. However, the related art extracts the context information of the sample to be processed using only a receptive field convolution of one size, i.e., using only neighborhood information within one range in the context model, and does not effectively eliminate encoding/decoding redundancy. Disclosure of Invention The application provides an image compression method, an image encoding method, an image decoding method and an image decoding device, which can effectively utilize neighborhood information in various ranges and can effectively eliminate encoding/decoding redundancy. In order to achieve the above object, the present application provides an end-to-end image compression method, which includes: carrying out convolution processing on the image characteristics to be processed based on the multiscale receptive field to obtain multiple context characteristics of the image characteristics to be processed; fusing the multiple context features to obtain sample features of the image features to be processed; and obtaining a compression result of the image to be compressed based on the sample characteristics of the image characteristics to be processed. In order to achieve the above object, the present application further provides an end-to-end image encoding method, which includes: Obtaining image characteristics to be processed based on the image characteristics of the image to be compressed; Processing the image characteristics to be processed by the image compression method to obtain a compression result of the image to be compressed; And obtaining the coding code stream of the image to be compressed based on the compression result. In order to achieve the above object, the present application further provides an end-to-end image decoding method, which includes: Decoding a code stream of an image to be compressed to obtain image characteristics of the image to be compressed; Processing the image characteristics to be processed in the image characteristics of the image to be compressed by the image compression method to obtain a compression result of the image to be compressed; and obtaining a decoded image of the code stream based on the compression result. To achieve the above object, the present application also provides an encoder including a processor for executing instructions to implement the steps of the above method. To achieve the above object, the present application also provides a decoder including a processor for executing instructions to implement the steps of the above method. To achieve the above object, the present application also provides a computer-readable storage medium storing instructions/program data capable of being executed to implement the above method. In the image compression method, the image features to be processed are subjected to convolution processing based on the multiscale receptive fields to obtain multiple context features of the image features to be processed, so that the multiple context features are fused to obtain sample features of the image features to be processed, and therefore the image compression method of the embodiment provides a multiscale receptive field mode, and by combining the multiscale receptive fields, neighborhood point information in different ranges is effectively utilized, coding/decoding redundancy can be effectively eliminated, and image processing efficiency can be improved. Drawings The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings: FIG. 1 is a schematic diagram of an embodiment of an image codec network according to the present application; FIG. 2 is a flow chart of an embodiment of an image compression method according to the present application; FIG. 3 is a schematic diagram of an embodiment of an image compression method according to the present application; FIG. 4 is a schematic diagram of another embodiment of the image compression method of the present application; FIG. 5 is a schematic diagram of a further embodiment of the image compression method of the present application; FIG. 6 is a flow chart of another embodiment of the image compression method of the present application; FIG. 7 is