A Fully Embedded Two-Stage Coder for Hyperspectral Near-Lossless Compression
Jente Beerten, Ian Blanes, Joan S. Serra-Sagrista · IEEE Geoscience and Remote Sensing Letters · 2015
This letter proposes a near-lossless coder for hyperspectral images. The coding technique is fully embedded and minimizes the distortion in the l2-norm initially and in the $l_\infty$-norm subsequently. Based on a two-stage near-lossless compression scheme, it includes a lossy and a near-lossless layer. The novelties are the observation of the convergence of the entropy of the residuals in the original domain and in the spectral-spatial transformed domain and an embedded near-lossless layer. These contributions enable a progressive transmission while optimizing both signal-to-noise ratio (SNR) and peak absolute error (PAE) performance. The embeddedness is accomplished by bit-plane encoding plus arithmetic encoding. Experimental results suggest that the proposed method yields a highly competitive coding performance for hyperspectral images, outperforming multicomponent JPEG2000 for the l∞-norm and pairing its performance for the l2-norm, and also outperforming M-CALIC in the near-lossless case, i.e., for PAE ≥ 5.