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Analysis of compression methods applied to hyperspectral images

机译:分析应用于高光谱图像的压缩方法

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摘要

Several well-known methods for lossy compression of still images are here analyzed to evaluate their performance for hyperspectral images. The lossy compression methods discussed are the JPEG standard, and four approaches based on the Wavelet Transform: the Embedded coding of ZeroTree wavelet coefficients, the Set Partitioning in Hierarchical Trees, a Lattice Vector Quantizer, and the new JPEG2K. Experiments are first performed on corpuses of natural grayscale still images to provide a general framework of the performance of each method. Then experiments are performed on several hyperspectral images taken with CASI and AVTRIS sensors. Experiments show that it is possible to employ the basic lossy compression methods for hyperspectral image coding. The wavelet-based approaches produce results consistently better than the JPEG: JPEG can not achieve compression ratios above 75:1; on the other side, with EZT, SPIHT and LVQ compression ratios of 250:1 or higher may be reached. For JPEG2K, higher compression ratios than JPEG may also be reached, but with a PSNR quality lower than the three other techniques. At compression ratios about 8:1, the wavelet methods yield results 1.5 dB better than those of JPEG. These results help to explain why JPEG2K standard uses the WT instead of the DCT.
机译:本文分析了几种已知的静止图像有损压缩方法,以评估其对高光谱图像的性能。所讨论的有损压缩方法是JPEG标准,以及基于小波变换的四种方法:ZeroTree小波系数的嵌入式编码,分层树中的集合划分,格向量量化器和新的JPEG2K。首先对自然灰度静态图像的语料库进行实验,以提供每种方法性能的一般框架。然后,对使用CASI和AVTRIS传感器拍摄的几幅高光谱图像进行实验。实验表明,可以将基本的有损压缩方法用于高光谱图像编码。基于小波的方法产生的结果始终优于JPEG:JPEG无法实现75:1以上的压缩率;另一方面,使用EZT时,可能会达到250:1或更高的SPIHT和LVQ压缩比。对于JPEG2K,也可以实现比JPEG更高的压缩率,但是PSNR质量低于其他三种技术。在约8:1的压缩率下,小波方法的结果比JPEG的结果好1.5 dB。这些结果有助于解释为什么JPEG2K标准使用WT而不是DCT。

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