Ternary-representation-based image predictive coding method

Abstract

The invention relates to a ternary-representation-based image predictive coding method, which is particularly suitable for the compression processing of static images. The method comprises the following steps of: performing wavelet transform and wavelet coefficient quantization on an image, representing each wavelet coefficient by using a ternary number and scanning a ternary wavelet coefficient plane; selecting a nearest-neighbor coefficient of a symbol currently to be coded as a prediction coefficient, defining an importance state function, an importance state direction weighting function and an importance state and function expression of the prediction coefficient for the characteristics of three symbols, and establishing a high-efficiency prediction model; and calculating a predicted value according to the prediction model, transmitting the symbol currently to be coded into a corresponding arithmetic coder for entropy coding, and resetting an initial value of the arithmetic coder between frequency bands. By the method, the high-efficiency predictive coding of wavelet coefficients is realized, and the objective quality of image recovery is effectively improved.

Description

technical field [0001] The present invention relates to a predictive encoding method suitable for static image compression, in particular to a wavelet coefficient predictive encoding method using ternary system to represent wavelet coefficients and establishing a corresponding predictive classification model to improve compression efficiency, which belongs to image compression technology field. Background technique [0002] In recent ten years, the image compression algorithm based on wavelet transform has been widely used in static image compression, and is considered to be the best compression performance method at present. Its compression process mainly includes four steps: preprocessing, wavelet transform, quantization, and entropy coding, such as figure 1 shown. Among them, entropy coding encodes the data according to the probability of occurrence of the data, which can remove the statistical redundancy between the data, so as to complete the representation of the ori...

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Problems solved by technology

However, if the selected base is too high, the amount of information contained in each plane will be large. On the one hand, this is not conducive to the priority encoding of important information according to the rate-distortion principle (because the granularity of information division becomes coarser), on the other hand, it may Insufficient utilization of correlation (the amount of information contained in each symbol becomes larger, including those coefficients that are scanned after the current symbol to be encoded, so that more prediction information cannot be used)

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