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Comparison of Several Lossless Image Compression and Coding Algorithms
Author: FengXi
Tutor: LiangYanBing
School: Xi'an Optics and Fine Mechanics
Course: Signal and Information Processing
Keywords: Lossless compression LOCO-I Integer Wavelet SPIHT
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 567
Quote: 6
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Abstract
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Lossless image compression means to reduce the amount of data obtained in the premise of no image loss , low - bit stream of the image data expressed . It is mainly used in some of the need to do further processing of the image , repeated compression and decompression , image acquisition expensive areas , such as fingerprint images , remote sensing image , medical image processing . For efficient, real-time image lossless compression requirements , a rapid study the image lossless compression techniques and algorithms have important theoretical significance and practical value . Today lossless compression of two representative algorithm , one is based on prediction and variable length encoding of the adaptive statistical context model LOCO-Ⅰ algorithm , it is the core of the standard of JPEG-LS ; another It is based on integer wavelet transform (5 / 3 and 9/7-M) and SPIHT zerotree coding algorithm . LOCO-Ⅰ algorithm the adaptive statistical context model prediction compared to the general fixed prediction , more effective in reducing the correlation between the pixels , Golomb encoding algorithm error is also very effective . Traditional wavelet transform, convolution operation is required , high complexity , it is difficult to achieve real-time processing hardware without convolution operation based on lifting the format integer wavelet transform not only , but also because of the process and results of each promotion integer , so that it can be applied in lossless compression , combined with the zerotree coding SPIHT algorithm thought DPCM and Huffman entropy coding can effectively transform the wavelet coefficients coding . Achieve two-part simulation : a simulation difference map and its statistical properties , JPEG and JPEG-LS predictor comparisons JPEG-LS predictor better than JPEG ; another integer wavelet transform and SPIHT encoded on the given image , and a typical test image lossless compression and coding simulation , three wavelet transform and the transform coefficients to achieve a 5/3 wavelet 9/7-M wavelet SPIHT coding , from the obtained encoded stream and the observation of the histogram of the wavelet coefficients can be seen : 9/7-M wavelet performance is better than 5 / 3 wavelet . Can be used as based on 9/7-M wavelet algorithm and LOCO-Ⅰ algorithm the fast image lossless compression algorithm is applied to the actual hardware circuit among .
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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