Lossless compression of hyperspectral imagery through 2D/3D hybrid prediction

被引：0

作者：

Chai, Y ^{[1
]}

Zhang, XL ^{[1
]}

Shen, LS ^{[1
]}

机构：

[1] Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China

来源：

INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS AND INFORMATION TECHNOLOGIES 2005, VOLS 1 AND 2, PROCEEDINGS | 2005年

关键词：

loss less compression; hyperspectral compression; hybrid prediction;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Using the significant spectral correlation within the hyperspectral images, we present a lossless compression algorithm in this paper. By means of hand ordering according to spectral correlation coefficient and 2D/3D hybrid predicton, which are based on local texture and neural networks, hyperspectral data are decorrelated. The prediction residuals are then entropy coded by context-based Golomb coding. Experimental results show that this method can remove the spatial and spectral redundancy efficiently and outperforms JPEG-LS and 3D-APA on average bit rate obviously.

引用

页码：1409 / 1412

页数：4

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