Robust hyperspectral image coding with channel-optimized trellis-coded quantization

• Published in: IEEE transactions on geoscience and remote sensing Vol. 40; no. 4; pp. 820 - 830
• Main Authors: Abousleman, G.P., Tuyet-Trang Lam, Karam, L.J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-04-2002; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied geophysics; Channel coding; Channels; Coders; Decoding; Design optimization; Earth sciences; Earth, ocean, space; Encoders; Errors; Exact sciences and technology; Hyperspectral imaging; Image coding; Internal geophysics; Noise levels; Noise robustness; Protection; Quantization; Security; Streaming media; optimization; multispectral remote sensing; data processing; noise; remote sensing; degradation; compression; errors; quality
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2002.1006360

This paper presents a wavelet-based hyperspectral image coder that is optimized for transmission over the binary symmetric channel (BSC). The proposed coder uses a robust channel-optimized trellis-coded quantization (COTCQ) stage that is designed to optimize the image coding based on the channel characteristics. This optimization is performed only at the level of the source encoder and does not include any channel coding for error protection. The robust nature of the coder increases the security level of the encoded bit stream, and provides a much higher quality decoded image. In the absence of channel noise, the proposed coder is shown to achieve a compression ratio greater than 70:1, with an average peak SNR of the coded hyperspectral sequence exceeding 40 dB. Additionally, the coder is shown to exhibit graceful degradation with increasing channel errors.