Distributed lossless compression of hyperspectral images based on multi-band prediction

被引：3

作者：

Nian, Yong-Jian ^{[1
]}

Xin, Qin ^{[1
]}

Tang, Yi ^{[1
]}

Wan, Jian-Wei ^{[1
]}

机构：

[1] College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China

来源：

Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2012年 / 20卷 / 04期

关键词：

Image coding - Spectroscopy - Thermography (imaging) - Hyperspectral imaging - Image compression;

D O I：

10.3788/OPE.20122004.0906

中图分类号：

学科分类号：

摘要：

A lossless compression algorithm based on distributed source coding was proposed to compress the airborne hyperspectral data effectively. In order to make full use of the spectral correlation of hyperspectral images, a multi-band prediction scheme was introduced to acquire the prediction values of the current block and to reduce the maximal absolute value of prediction error effectively. Then, by using the maximal absolute value to determine the coset index of pixels belonging to the current block, the lossless compression of hyperspectral images was realized by transmitting the coset index of the current block instead of its prediction error. Experimental results on hyperspectral images acquired by Airborne Visible Infrared Imaging Spectrometer (AVIRIS) show that the proposed algorithm can offer both high compression performance and low encoder complexity compared with those existing classical algorithms, which is available for on-board compression of hyperspectral images.

引用

页码：906 / 912