Title :
A Novel Lossless Compression for Hyperspectral Images by Adaptive Classified Arithmetic Coding in Wavelet Domain
Author :
Jing Zhang ; Guizhong Liu
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´an Jiaotong Univ., China
Abstract :
In this paper, we propose a lossless compression algorithm for hyperspectral images; it is based on the adaptive classified arithmetic coding in wavelet domain and the adaptive spectral band reordering algorithm. The adaptive classified scheme divides each of the residual images after wavelet transform into different classes, and then the adaptive arithmetic coding is performed for each of the classes. This classified coding scheme saves a lot of coding bits. The adaptive spectral band reordering algorithm finds out the nearly best reference band for each of the bands, so the spectral correlation is better used. Combining these two algorithms makes full use of the characteristics of hyperspectral images. Experiments show that our method is capable of providing a high compression performance.
Keywords :
adaptive codes; arithmetic codes; correlation methods; data compression; image classification; image coding; wavelet transforms; adaptive classified arithmetic coding; adaptive spectral band; hyperspectral image; lossless compression algorithm; reordering algorithm; spectral correlation; wavelet domain; Arithmetic; Compression algorithms; Discrete wavelet transforms; Hyperspectral imaging; Hyperspectral sensors; Image coding; Layout; Pixel; Wavelet domain; Wavelet transforms; arithmetic codes; image coding; remote sensing; wavelet transforms;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312815