Decorrelation of multispectral images for lossless compression

Rong Zhang; Zhengkai Liu; Nenghai Yu

doi:10.1117/12.442914

26 September 2001 Decorrelation of multispectral images for lossless compression

Rong Zhang, Zhengkai Liu, Nenghai Yu

Proceedings Volume 4551, Image Compression and Encryption Technologies; (2001) https://doi.org/10.1117/12.442914
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

Decorrelation is the most important step in lossless compression. There are spatial and spectral redundancies in multispectral images. In this paper, we proposed a new technique that integer wavelet transform is used to remove spatial redundancy and non-linear predictors are used to remove spectral redundancy. For computational reason, the number of spectral predictors is discussed. These techniques result in higher compression ratios.

Citation Download Citation

Rong Zhang, Zhengkai Liu, and Nenghai Yu "Decorrelation of multispectral images for lossless compression", Proc. SPIE 4551, Image Compression and Encryption Technologies, (26 September 2001); https://doi.org/10.1117/12.442914

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