Quick fractal video compression and decompression method

Abstract

The invention provides a quick fractal video compression and decompression method, comprising the following steps: firstly, coding an initial frame by block DCT (discrete cosine transformation); carrying out block movement estimation / compensation coding on a non-I frame; calculating the pixel sum and the pix quadratic sum of a sub block relevant to a sub block region and a father block region; meanwhile, calculating the pixel sum and the pixel quadratic sum of the interpolated value corresponding block of a subpixel; then, carrying out preview search restricted condition judgment; finding the most similar matching block in a previous frame of search window by an unsymmetrical cross-shaped multi-level hexagon lattice point search algorithm matched and improved by a subpixel block; and finally, compressing an iterated function system coefficient by a Huffman coding method. The corresponding decompression process comprises the following steps: decoding the I frame in an inverse DCT mode; performing Huffman decoding on the non-I frame to obtain the iterated function system coefficient; then, decoding on the basis of a macroblock; calculating the pixel sum and the pixel quadratic sum of a relevant sub block in the father block region; then, successively decoding each macroblock in the current frame; and utilizing a deblocking loop filter method.

Description

technical field [0001] The invention belongs to the field of video compression coding in signal processing, and especially proposes a fast fractal video compression coding method for the field of new generation video coding, which greatly accelerates the speed and compression ratio of fractal video coding on the premise of ensuring image quality. 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 Interna...

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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