Image compression encoding and decoding devices without visual loss, and encoding and decoding methods

Abstract

The invention discloses an image compression encoding and decoding devices without visual loss, and encoding and decoding methods. The encoding method involves, first of all, dividing each row of an image into a plurality of micro-blocks, analyzing the micro-blocks, and determining the types of the macro-blocks; performing graphic encoding on graphic-type micro-blocks, performing intraframe mode prediction on non-graphic-type micro-blocks, and solving residual errors between current macro-blocks and predicted macro-blocks; analyzing the residual errors, and performing wavelet transformation on the residual errors needing wavelet lifting to obtain transformation coefficients; then according to image content, adaptively performing code rate control, and forming bit surface encoding on the input residual errors or the transformation coefficients to obtain final code rates; and finally, through combination with the predicted macro-blocks, reconstructing the macro-blocks. According to the invention, the purpose of high-quality and high-speed transmission of a single row of the image at a constant code rate is achieved, the image after compaction and an original image are free from the visual loss, the complexity is quite low, and fewer resources are occupied.

Description

technical field [0001] The present invention relates to an image compression encoding and decoding device and encoding and decoding method, in particular to a visually lossless image compression encoding and decoding device and encoding and decoding method. Background technique [0002] In today's digital age, a lot of information is expressed, transmitted and stored digitally. Image is a medium that contains the largest amount of information, but the huge amount of information in digital images has also become an obstacle in the process of digitization, and effective compression must be carried out. For the storage and transmission of image data such as remote sensing photos, reconnaissance photos, fingerprint images, medical images, weather cloud images, etc., in order not to lose key information and facilitate later processing and application, lossless compression is often used. Especially in the development process of chips and hardware, due to the limitation of DDR ban...

AI Technical Summary

Problems solved by technology

Especially in the development process of chips and hardware, due to the limitation of DDR bandwidth, it is impossible to smoothly read, write, store, and cache high-resolution video images (such as 1080P, 4k*2k) Lossless or near-lossless compression

[0003] Commonly used general lossless data compression algorithms include LZW, Huffman coding, arithmetic coding, etc., and the existing lossless compression standards for single-frame images include JPEG2000, JPEG-LS, etc., but the above algorithms have certain defects to varying degrees, such as Algorithms such as Huffman coding, arithmetic coding, and JPEG2000 have high compression rates, but they are also highly complex and difficult to implement. Algorithms such as LZW have low complexity and fast speed, but low compression rates. Algorithms such as JPEG-LS are implemented by hardware. tougher

It can be seen that the existing mature schemes cannot fundamentally solve the above-mentioned various problems, and it is necessary to propose a lossless compression scheme with higher efficiency and lower complexity

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