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Compression of Hyper-Spectral Images and Its Performance Evaluation

机译:压缩超光谱图像及其性能评估

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Effective lossy algorithms for compressing hyperspectral images using singular value decomposition (SVD) and discrete cosine transform (DCT) have been presented in this paper. A Hyperspectral image consists of a number of bands and each band contains some specific information. This paper suggests two compression algorithms that are used to compress the hyperspectral images by considering hyperspectral image data, band-by-band and applying compression to each band employing SVD and DCT. The compression performance of the resultant images are evaluated using various objective image quality metrics and are found to be attractive for hyperspectral image compression.
机译:本文已经提出了用于使用奇异值分解(SVD)和离散余弦变换(DCT)来压缩高光谱图像的有效损耗算法。高光谱图像由许多频带组成,每个频带包含一些特定信息。本文提出了两个压缩算法,用于通过考虑高光谱图像数据,横频带和应用于采用SVD和DCT的每个频带来压缩高光谱图像。使用各种物镜图像质量指标评估所得到图像的压缩性能,并且被发现对高光谱图像压缩具有吸引力。

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