Low complexity DCT-based distributed source coding with Gray code for hyperspectral image

Abstract

Hyperspectral image compression demands simple onboard encoder. Contrary to most distributed source coding (DSC) compression methods in wavelet transform (WT) domain, we propose a low complexity discrete cosine transform (DCT)-based DSC paradigm with Gray code. We use a set-partitioning approach on reorganized DCT coefficients to extract bitplanes; then we apply Gray code to refinement bits; lastly low density parity check (LDPC)-based Slepian-Wolf coder is implemented to our DSC strategy. Hence the coding strategy shifts the complexity from encoder to decoder. Experimental results for AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data illustrate that the proposed scheme can improve up to 2dB better than DSC-based coder in WT domain, regardless of the using DCT-based coder worse than wavelet-based one. It also reaches up to 6dB by comparison with that independently using 2-Dimensional (2D) DCT-based coder.