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.
Highlights
Hyperspectral images provide finer spectral information traditional multispectral images
To evaluate the performance of a Multimodal Compression scheme using 3D-SPIHT on a sequence of hyperspectral images, experiences have been performed according to the following three phases: 1) Comparison phase: 3D-SPIHT is compared to standards such as: CCSDS (The Consultative Committee for Space Data Systems) [12] and JPEG 2000 [4,6]
Comparison phase As evoked above, 3D-SPIHT is compared in terms of bit-distortion to both CCSDS standard and JPEG 2000
Summary
Hyperspectral images provide finer spectral information traditional multispectral images. The volume of generated data is dramatically huge. Data compression becomes essential for economical distribution when spaceborn hyperspectral data are regularly available. The term hyperspectral is generally used for spectral data containing hundreds of samples of spectra. The hyperspectral images present specific characteristics that require to be exploited by some specific compression algorithms [1]. Since hyperspectral sequence images consider a set of images, they can be regarded somehow as volumetric data requiring specific techniques of compression
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