Research on Hyperspetral Image Compression Based on 3D SPIHT Algorithm

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Research on Hyperspetral Image Compression Based on 3D SPIHT Algorithm

Article | 更新时间：2020-08-12

- Research on Hyperspetral Image Compression Based on 3D SPIHT Algorithm
- Optics and Precision Engineering Vol. 16, Issue 6, Pages: 1146-1152(2008)
- 作者机构：
  
  国防科技大学电子科学与工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Received：12 December 2007，
  
  Revised：20 February 2008，
  
  Published Online：25 June 2008，
  
  Published：25 June 2008
- 稿件说明：
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粘永健,辛勤,孙蕾,万建伟. 基于3D SPIHT的高光谱图像压缩技术研究[J]. 光学精密工程, 2008,16(6):1146-1152

Research on Hyperspetral Image Compression Based on 3D SPIHT Algorithm[J]. Optics and precision engineering, 2008, 16(6): 1146-1152.
粘永健,辛勤,孙蕾,万建伟. 基于3D SPIHT的高光谱图像压缩技术研究[J]. 光学精密工程, 2008,16(6):1146-1152 DOI：

Research on Hyperspetral Image Compression Based on 3D SPIHT Algorithm[J]. Optics and precision engineering, 2008, 16(6): 1146-1152. DOI：

摘要

高光谱图像作为一种三维图像，其海量数据给存储和传输带来了极大的困难，必须对其进行有效压缩。本文将三维多级树集合分裂（3D SPIHT）算法应用于高光谱图像的压缩。首先根据高光谱图像的特点进行波段分组以得到处理单元，对各组分别进行三维小波变换，去除谱间和谱内冗余，利用3D SPIHT算法对变换后小波系数进行编码，去除系数之间的冗余。通过采用整数小波和浮点小波分别进行无损和有损压缩仿真，实验结果表明，3D SPIHT算法有损压缩较好，且算法具有嵌入式、可伸缩性等优点，但无损压缩性能要逊于基于预测的方法。

Abstract

As 3D image

the data size of hyperspectral image is too large for storage or transmission

so it is necessary to compress hyperspectral image efficiently. In this paper

3D SPIHT is applied to hyperspectral image compression. Firstly

band grouping is performed to obtain the processing unit

and then the three dimensional wavelet transform is applied to each group to eliminate both spatial and spectral redundancy. Finally

3D SPIHT algorithm is used to encode the wavelet coefficients. Both integer and float wavelet are used for lossless and lossy compression respectively. Experimental results show that the proposed algorithm has better lossy coding performance

while lower lossless coding performance than predictive coding technique.

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Related Institution

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