基于提升方案的陆地卫星图像压缩

L. L. M. Paul Shoba, V. Mohan, Y. Venkataramani
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引用次数: 3

摘要

本文首先对Landsat图像进行Karhunen Loeve变换去除光谱相关性,然后对Landsat图像进行小波变换去除空间相关性,最后进行编码。一种方法采用双正交小波,另一种方法采用Haar小波提升格式。分别应用SPIHT和EZW方法进行编码,并对编码结果进行比较。计算相关系数来验证频谱去相关,并以比特率测量压缩,计算压缩比和峰值信噪比。利用Landsat图像进行实验,发现KLT的相关系数有所降低,是一种有效的光谱去相关方法。在压缩比方面,采用KLT、Lifting方案、EZW方案的压缩方法比其他压缩方法具有更好的效果。在比特率方面,使用KLT、双正交小波、SPIHT的压缩方法比其他压缩方法具有更好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Landsat image compression using lifting scheme
In this paper, Karhunen Loeve transform is applied to the Landsat image for removing the spectral correlation, and then wavelet transform is applied for removing spatial correlation followed by which coding is done. Biorthogonal wavelets are applied in one method and lifting scheme using Haar wavelet is applied in another method. SPIHT and EZW are applied for coding in each of the two methods and the results are compared. The correlation coefficient is calculated to verify spectral decorrelation and the compression is measured in terms of bit rate, compression ratio and peak signal to noise ratio is calculated. The experiment was tested with the Landsat images and found that the correlation coefficient has been reduced and hence KLT is effective for spectral decorrelation. In terms of compression ratio, the compression approach using KLT, Lifting scheme, EZW provides better results than other compression approaches. In terms of bit rate, the compression approach using KLT, Biorthogonal wavelet, SPIHT provides better results than other compression approaches.
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