Image lossless compression method on basis of Huffman code

Abstract

The embodiment of the invention discloses an image lossless compression method on the basis of a Huffman code. In the image lossless compression method, an optimal coding method can be obtained by adopting an optimal coding theorem of alterable word length coding according to an inverted sequence distribution code word length of the appearance probabilities of characters, and a code is given to each character by the Huffman code so as to form a coding table, wherein the coding table needs to be stored and in the decoding process, the coding table needs to be referred to so that the decoding can be correctly carried out; and the Huffman code is a different prefix code, and thus, in the decoding process, as long as a binary sequence with a certain length can be matched with the code in the coding table, the sequence is the code of one character, so that the unique decoding property is ensured. Due to the adoption of the image lossless compression method on the basis of the Huffman code, the rapid search is realized by decreasing the times of logic judgment and increasing a small quantity of space for storing the coding table, the coding table and a decoding table are respectively stored at a coding end and a decoding end, and the table lookup is directly carried out in the coding process, so that a great amount of judging time is saved.

Description

Technical field [0001] The invention relates to the field of digital image compression, in particular to a lossless image compression method based on Huffman coding. Background technique [0002] The traditional image coding technology is also called the first generation coding technology, mainly including predictive coding, transform coding, information coding and vector quantization. Predictive coding and transform coding are the most commonly used technologies in current image encoders. The main purpose of prediction and transform is to reduce the strong correlation in the original spatial domain representation of the image, so that the predicted or transformed data matrix becomes a weak correlation matrix. In this way, scalar quantization and direct coding can be used for effective compression. Information coding is a kind of distortion-free coding. There are three commonly used ones: Huffman Coding, Run Length Coding and Arithmetic Coding. [0003] With the popularization of...

AI Technical Summary

Problems solved by technology

Obviously, the disadvantage of this model is that for information with a large amount of data, it takes a lot of time to scan repeatedly, and the coding tree must be stored in order to construct the same coding tree when decoding, which will consume a lot of space and reduce the compression efficiency

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