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首页> 外文学位 >Classification performance of hyperspectral images using the discrete wavelet transform with color and quality scalability under JPEG2000.
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Classification performance of hyperspectral images using the discrete wavelet transform with color and quality scalability under JPEG2000.

机译：在JPEG2000下使用具有颜色和质量可伸缩性的离散小波变换对高光谱图像进行分类的性能。

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摘要

The classification performance of hyperspectral images using two different forward transforms is investigated. The tradeoff between the Discrete Wavelet Transform (DWT) and the Principal Component Analysis (PCA) is measured using different compression algorithms found in the JPEG2000 standard. These cross-component transforms can be evaluated in order to obtain a comparison of how well each transform can decorrelate data, reorder data optimally, speed of implementation, and effect on mineral classification performance. In addition, two scalability options defined by JPEG2000 were used: color and quality. Compression algorithms were carried out for the DWT and the PCA using the same set of parameters; the same hyperspectral image, the same classification algorithm---Spectral Angle Mapper, and the same type of compression: lossless compression. The purpose of this comparison is to be able to determine how much partial decompression is needed in order to achieve a 90% hit rate when classifying several minerals. This evaluation is focused primarily on two types of Mica called Aluminum-rich and Aluminum-poor Mica. The DWT yielded a compression performance almost as good as that of the PCA; for example, the 90% hit rate mark was achieved when using less than double the number of component bands with color scalability and less than triple with quality scalability for the DWT. On the other hand, this transform was about seven times faster than the PCA.
机译：研究了使用两个不同的正向变换的高光谱图像的分类性能。离散小波变换（DWT）和主成分分析（PCA）之间的权衡是使用JPEG2000标准中发现的不同压缩算法来衡量的。可以对这些跨分量转换进行评估，以便比较每个转换可以对数据进行去相关，最佳地对数据进行重新排序，实现的速度以及对矿物分类性能的影响。另外，使用了JPEG2000定义的两个可伸缩性选项：颜色和质量。 DWT和PCA使用相同的参数集执行压缩算法；相同的高光谱图像，相同的分类算法-光谱角度映射器和相同的压缩类型：无损压缩。该比较的目的是能够确定对几种矿物进行分类时需要多少部分减压才能达到90％的命中率。该评估主要针对两种类型的云母，即富铝云母和贫铝云母。 DWT产生的压缩性能几乎与PCA相同。例如，当DWT使用的色带数量少于组件带数量的两倍时，质量可缩放性少于组件带数量的三倍时，命中率达到90％。另一方面，这种转换比PCA快大约7倍。

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