Efficient Inter-Band Prediction and Wavelet Based Compression for Hyperspectral Imagery: A Distributed Source Coding Approach

Hyperspectral images have correlation at the level of pixels; moreover, images from neighboring frequency bands are also closely correlated. In this paper, we propose to use distributed source coding to exploit this correlation with an eye to a more efficient hardware implementation. Slepian-Wolf and Wyner-Ziv based correlated coding theorems have quantified how much additional rate reduction can be obtained. In order to better exploit these correlations, we first propose a prediction model to align images. This model is based on linear prediction techniques and it is simple and shown to be effective for hyperspectral images. We then propose a coding scheme to exploit these correlations. A set-partitioning approach is used on wavelet transformed data to extract bitplanes. Under our correlation model, bitplanes from neighboring bands are correlated and we then use a low-density parity-check based Slepian-Wolf code to exploit this bitplane level correlation. This scheme is appealing for...

• Type: Conference
• Year: 2005
• Where: DCC
• Authors: Caimu Tang, Ngai-Man Cheung, Antonio Ortega, Cauligi S. Raghavendra
• Keywords: Bitplane Level Correlation, Computer Graphics, Correlated Coding Theorems, Correlation Spectral Bands, DCC 2005