基于分段K-L变换的遥感图像压缩

提出了基于分段Karhunen-Loeve变换和整数小波的遥感图像压缩方法。算法的关键是依据高光谱图像的谱间相关性,改变K-L变换的谱段间隔数。与传统的K-L变换相比,改进的分段式的K-L变换使用了较少的相邻谱段,所以能更快更好地恢复原图像。实验结果表明分段式的K-L变换/整数小波变换的图像压缩方法比传统K-L变换/整数小波变换具有更好的性能。由国家自然科学基金项目(60472081);; 厦门大学985二期信息创新平台项

A New Quasi-Lossless Compression of Partitioned KLT and IWT Multispectral Images

提出了分组Karhunen-Leove变换(KLT)和整数小波变换(IWT)的高光谱图像数据压缩方法,并采用整数小波变换技术和Set Partitioning in Hierarchical Trees(SPIHT)压缩编码,实现了对分组Karhun-Loeve变换后的数据压缩。该压缩编码方法与现有压缩方法相比,既保留了Karhun-Loeve变换压缩性能和整数小波变换高压缩比的特点,也宜于实时传输。实验结果表明,分组Karhun-Loeve变换/整数小波变换/SPIHT在相同压缩比下,峰值信噪比比Karhun-Loeve变换/小波变换/WSFCVQ、Karhun-Loeve变换/小波变换/改进的对块零树编码压缩和Karhun-Loeve变换/WT/FSVQ分别提高了6 dB,9 dB和8 dB,运算时间减少一半,整体压缩性能有了较大的提高。A method of hyperspectral image data compression using partitioned Karhunen-Loeve transform(PKLT) and integer wavelet transform(IWT) is proposed.IWT technique and set partitioning in hierarchical trees(SPIHT) compression coding are used to compress the PKLT data.In comparison with other methods,PKLT/IWT/SPIHT not only reserves the compression performance of KLT and the performance of IWT's high compression rate,but also is easy to implement real-time transmission.Experimental results show that the peak signal-to-noise ratio(PSNR) of PKLT/IWT/SPIHT improves 6 dB,9 dB and 8 dB comparing with KLT/WT/WSFCVQ,KLT/WT/IBBZTC and KLT/WT/FSVQ in the condition of same compression rate respectively,computation hours decrease half,and the whole compression performance is enhanced much more.国家自然科学基金(60472081);; 厦门大学信息技术985二期信息创新平台项目(2004-2007)资助课