Coding of hyperspectral imagery using adaptive classification and trellis-coded quantization

Glen P. Abousleman

doi:10.1117/12.280597

4 August 1997 Coding of hyperspectral imagery using adaptive classification and trellis-coded quantization

Glen P. Abousleman

Proceedings Volume 3071, Algorithms for Multispectral and Hyperspectral Imagery III; (1997) https://doi.org/10.1117/12.280597
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

A system is presented for compression of hyperspectral imagery. Specifically, DPCM is used for spectral decorrelation, while an adaptive 2D discrete cosine transform coding scheme is used for spatial decorrelation. Trellis coded quantization is used to encode the transform coefficients. Side information and rate allocation strategies are discussed. Entropy-constrained codebooks are designed using a modified version of the generalized Lloyd algorithm. This entropy constrained system achieves a compression ratio of greater than 70:1 with an average PSNR of the coded hyperspectral sequence approaching 41 dB.

Citation Download Citation

Glen P. Abousleman "Coding of hyperspectral imagery using adaptive classification and trellis-coded quantization", Proc. SPIE 3071, Algorithms for Multispectral and Hyperspectral Imagery III, (4 August 1997); https://doi.org/10.1117/12.280597

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