计算机科学 ›› 2012, Vol. 39 ›› Issue (Z11): 395-397.

• 图形图像 • 上一篇    下一篇

一种基于Contourlet变换的高光谱图像压缩算法

白璘,刘盼芝,李光   

  1. (长安大学电子与控制工程学院 西安710064)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Hyperspectral Images Compression Algorithm Based on Contourlet Transform

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出了一种基于Contourlct变换的高光谱图像压缩算法,其将多尺度几何分析用于高光谱图像的空间去相关,在进行有损压缩时有效地保存了高光谱图像丰富的纹理信息。该算法首先对高光谱图像的每一个波段图像进行基于小波的Contourlet变换,然后用前一波段的变换系数预测当前波段,最后对预测误差进行SPIHT编码,形成嵌入式码流。实验结果表明,提出的基于Contourlct变换的高光谱图像压缩算法其压缩效果优于对比算法,且能较好地保留高光谱图像的纹理信息。

关键词: 高光谱图像压缩,多尺度几何分析,Contourlct, SPIH T编码

Abstract: The hyperspectral images compression algorithm based on contourlet transform is proposed, which using multiscale geometric analysis for hyperspectral image space de-correlation. Firstly, wavelet based contourlet transform on each band of hyperspectral images, then predict current band by transform coefficients of the previous band. Finally,SPIHT coder used on prediction error and embedded data stream generated. Experimental results show that the proposed algorithm based on contourlet transform achieve well compression efficient and retain high spectral image texture information better than comparison algorithm.

Key words: Hyperspectral image compression, Multiscale geometric analysis, Contourlet, SPIHT coder

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