Hyperspectral image coding and transmission scheme based on wavelet transform and distributed source coding

Abstract

This paper presents a novel scheme for satellite hyperspectral images broadcasting over wireless channels. First, a simple pre-processing is performed. Then, a new hyperspectral band ordering algorithm that improves the compression performance is implemented. The ordered image data is also normalized. The discrete wavelet transform with three-level decomposition is used to divide each hyperspectral image band into ten wavelet sub-bands; nine of them are the details and the last LL-LL-LL is an approximation version of the band. Coset coding based on distributed source coding (DSC) is used for the LL-LL-LL sub-band to achieve high compression efficiency and low encoding complexity. Then, without syndrome coding, the transmission power is allocated directly to the band details and coset values according to their distributions and magnitudes without forward error correction (FEC). Finally, these data are transformed by the Hadamard matrix and transmitted over a dense constellation. Satellite hyperspectral images from an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) satellite are used for the validation of the proposed scheme. Experimental results demonstrate that the proposed scheme improves the average image quality by 6.91, 3.00 and 7.68 dB over LineCast, SoftCast-3D, and Softcast-2D, respectively. It also achieves up to a 5.63 dB gain over JPEG2000 with FEC.