Image compression framework combining super-resolution and residual coding technology

Abstract

The invention discloses an image compression framework combining super-resolution and residual coding technology. The method includes establishing the mapping relationship of an original image and a sampling image compressed in different coding rate in an offline state, and constructing a super-resolution reconstruction model under each coding frequency; sampling the original image under iteration back projection to obtain the sampled small image; compressing the small image via a third-party encoder and transmitting the code stream and the de-noising auxiliary information; reconstructing the decoded small image into a big image at the decoding end by means of the super-resolution reconstruction model; suppressing the compressed noise in the big image through the combination with the de-noising auxiliary information; calculating the residual of the decoded big image and the original image at the coding end and transmitting the residual to the decoding end by means of the residual coding technology; and decoding the residual image at the decoding end, overlapping with the decoded big image, and recovering the final decoded image. An experiment shows that the framework provided can realize the compression ratio higher than JPEG2000.

Description

technical field [0001] The invention relates to image super-resolution and image compression technology, in particular to an image compression framework combined with super-resolution and residual coding technology, and belongs to the field of image communication. Background technique [0002] Images are an indispensable information carrier in human production and life, and the development of related technologies and industries has put forward increasingly demanding requirements for image quality. High-quality images often occupy a large amount of storage space, and also consume a huge amount of data traffic during network transmission, resulting in insufficient channel bandwidth. In this regard, classic image compression technologies, such as JPEG and JPEG2000, can compress the amount of data to the greatest extent while ensuring image quality as much as possible. However, with the emergence of high-definition and ultra-high-definition images, along with the limitations of...

AI Technical Summary

Problems solved by technology

Although the encoding performance of mainstream compression standards such as JPEG and JPEG2000 has been surpassed by more and more rising stars, it is impossible to be completely replaced in a short time because a large number of systems and devices in the multimedia field still maintain a strong dependence on them.

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