Computer Science ›› 2015, Vol. 42 ›› Issue (Z11): 140-141.

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Image Compression Based on Discrete Hermite Polynomials

XIAO Bin, LU Gang, WANG Guo-yin and MA Jian-feng   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Image compression can effectively decrease information redundancy among image’s pixels,and also ensure its reconstruction quality and lower computation complexity.The transform domain image compression coding is the most commonly used and one of the most optimal compression technology,but the image compression methods based on discrete orthogonal polynomials transform have not yet been deeply studied.Through studying the procedures of encoding and decoding of JPEG,we proposed an image compression algorithm based on discrete Hermite polynomials.Quantization table was determined depending on the ratio of the information entropy of the transform core and that of DCT.At last the results of quantization were encoded by using Huffman entropy coding.We realized the whole process of image compression and reconstruction based on discrete Hermite polynomials.The experimental results show that the algorithms are of similar compression ratio,share similar performance and the difference in peak signal noise ratio(PSNR) is small compared with the mainstream JPEG image compression standard.

Key words: Discrete hermite transform,JPEG,Image compression,Peak signal noise ratio(PSNR)

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