Fractal-based video compression and decompression method

Abstract

The invention provides a fractal-based video compression and decompression method. The compression method is a novel video compression and encoding method which adopts the fractal iteration principle for video encoding, and comprises the following steps: encoding a starting frame through block-DCT transformation, and carrying out block motion estimation / compensation coding for a non-I frame, which comprises calculating the sum and sum of squares of the pixels of sub-blocks related to sub-block domains and parent-block domains, finding a most similar matching block in a previous frame search window through full search, and finally compressing factors of an iteration function system through Huffman encoding. The corresponding decompression method comprises the following steps: decoding the I frame through anti-DCT transformation, carrying out Huffman decoding for the non-I frame to obtain the factors of the iteration function system, and carrying out macroblock-based decoding, which comprises calculating the sum and sum of squares of the pixels of the sub-blocks relevant to the parent-block domains, and decoding the macroblocks in the current frame in sequence. The method improves the traditional method of fractal video compression, and not only greatly increases the compression ratio and the peak signal-noise ratio, but also improves the encoding speed, thereby enhancing the fractal video compression and decoding performance, and making the fractal video compression and decoding more practical.

Description

technical field [0001] The invention belongs to the field of video compression coding in signal processing, and especially proposes a new fractal video compression coding method for the field of new-generation video coding. On the premise of ensuring image quality, the speed and compression ratio of fractal video coding are greatly accelerated. Background technique [0002] The fractal theory was first proposed by Mandelbrot in the 1970s (see B. Mandelbrot. The Fractal Geometry of Nature [M]. New York: W.H. Freeman and Company, 1982.). The mathematical basis of fractal coding is the iterative function system (IFS) theory. Barnsley first used fractal coding for interactive image compression (see Michael F. Barnsley, Alan D. Sloan. A better way to compress image [J]. Byte Magazine, 1988, 13(1): 215-233.). Jacqain proposed a fully automatic fractal image compression method (see Arnaud E. Jacquin. A novel fractal blocking-coding technique for digital image [C]. IEEE Internati...

AI Technical Summary

Problems solved by technology

However, in the cyclic predictive coding (CPM) method, in order to ensure that the initial frame can approximately converge to the original image after its own cyclic decoding, the compression process needs to go through complex transformations, searches, and iterations, etc., and the compression time and image quality are difficult to meet the requirements.

At present, the typical fractal image and video compression method has a large amount of calculation, the encoding speed is slow, and the quality of decoding needs to be improved, so the fractal image and video compression method needs further improvement and improvement

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