By Topic

A Novel Lossless Compression for Hyperspectral Images by Adaptive Classified Arithmetic Coding in Wavelet Domain

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jing Zhang ; School of Electronic and Information Engineering Xi'an Jiaotong University, Xi'an, China, 710049. Email: ; Guizhong Liu

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.

Published in:

2006 International Conference on Image Processing

Date of Conference:

8-11 Oct. 2006