A Fast Fractal Compression and Decompression Method for Multi-eye Stereo Video

Abstract

The invention provides a rapid fractal compression and decompression method for multi-cast stereo video. The method comprises the following steps of: selecting an intermediate cast as a reference cast; and compressing the intermediate cast by using a motion compensation prediction (MCP) principle and compressing other casts by using a principle of disparity compensation prediction (DCP) and MCP. Three casts are taken for example; the intermediate cast is used as the reference cast and is coded by a separate MCP mode; an initial frame is subjected to block discrete cosine transform (DCT) transform coding, and non-I frames are subjected to block motion estimation / compensation coding; a pixel sum and a pixel quadratic sum of a subblock related to a subblock domain and a father block domain are calculated; a pixel sum and a pixel quadratic sum of an interpolation corresponding block in a subpixel are calculated; a pre-search limiting condition is judged; and the most similar block is searched in a front frame search window through subpixel block matching and an adaptive hexagonal search algorithm based on a motion vector field. According to the method, the MCP mode and the DCP mode are adopted for coding left casts and right casts, the subpixel block matching and disparity distribution constraint condition are utilized during coding of the DCP mode, and deblocking loop filtering is adopted during decoding.

Description

Technical field: [0001] The invention belongs to the field of video compression coding, relates to compression coding of multi-eye stereo video, lays a foundation for the real-time application of stereo video coding, and further improves the performance of fractal multi-eye stereo video compression coding. 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 International Conference on Acoustics, Speech a...

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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