Research on Hyperspectral Remote Sensing Image Compression Algorithm

In the earth-observing system, hyperspectral remote sensing images are important data resource. They have a wide range of application in the national economy and development of society. The hyperspectral images which have three dimensions are very huge. It is hard to transmit and restore. So the hyperspectral remote sensing images must be compressed in applications. The existed image compression standards are for ordinary two-dimension images. There isn't any authoritative compression method for hyperspectral remote sensing images. In this paper, algorithms of hyperspectral remote sensing image compression are proposed.The correlation of hyperspectral remote sensing images is tested at first. The results show: The hyperspectral remote sensing images have much stronger spectral statistical correlation and spectral structure correlation than the RGB color images do. The spatial correlation of hyperspectral remote sensing images is weaker than that of ordinary images. In the compression algorithm design, the central focus is to get rid of the spectral correlation.The NMST (Near Minimum Spanning Tree) algorithm is proposed based on the MST (Minimum Spanning Tree) algorithm. The construction time of MST is too long when the image is large. This is improved in the NMST algorithm. ...

Article Submitted On: 06-28-2011

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