DocumentCode :
2958524
Title :
Adaptive image pyramid based compression algorithm
Author :
Dube, Simant ; Hong, Li
Author_Institution :
AST San Diego Lab., STMicroelectron. Inc., San Diego, CA, USA
Volume :
2
fYear :
2000
fDate :
Oct. 29 2000-Nov. 1 2000
Firstpage :
1045
Abstract :
We present a novel and fast algorithm to compress an image using nonlinear wavelets under a nonexpansive image pyramid framework. An image pyramid is constructed by downsampling the image and by computing the difference pyramid by upsampling a lower resolution image to predict the next higher resolution image. The novelty of the method lies in using a nonlinear adaptive method to upsample the image, and in processing of the prediction difference in order to reduce its entropy. Performance of the lossless compression is comparable or only slightly worse than the best lossless compression algorithms such as CALIC and LOCO-I, and it also has the additional feature of multiresolution format. The algorithm also works well in lossy mode and it has superior performance on mixed text/graphics images than SPIHT and JPEG.
Keywords :
adaptive codes; data compression; image coding; image resolution; image sampling; transform coding; wavelet transforms; difference pyramid; fast algorithm; grayscale images; higher resolution image; image compression; image downsampling; image upsampling; lossless compression; lossy compression; lower resolution image; multiresolution format; nonexpansive image pyramid framework; nonlinear adaptive method; nonlinear wavelets; Compression algorithms; Entropy; Floating-point arithmetic; Frequency; Image coding; Image resolution; Nonlinear filters; Performance loss; Transform coding; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
ISSN :
1058-6393
Print_ISBN :
0-7803-6514-3
Type :
conf
DOI :
10.1109/ACSSC.2000.910674
Filename :
910674
Link To Document :
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