Fast Encoding-Decoding of 3D Hyperspectral Images Using a Non-Supervised Multimodal Compression Scheme
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Abstract
We introduce in this paper an extension of the Multimodal Compression technique (MC) for the purpose of coding hyperspectral image sequences. The main idea requires few steps, namely: (1) reducing the size of the sequence by inserting smooth images containing less information into the remaining images of the same sequence, (2) then coding the new compacted sequence using 3D-SPIHT algorithm. In this new scheme, called MC-3D-SPIHT, the insertion is achieved only in the contour of each image, according to a non-supervised way, so that one can preserve the Region of Interest (ROI) quality. For this purpose, a mixing function is employed. After the decoding process, inserted images are extracted by a separation function and the original sequence is reconstructed. By considering data from AVIRIS database, we will show how one decrease significantly the computing time for both coding and decoding.
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