Title :
Robust hyperspectral image coding with channel-optimized trellis-coded quantization
Author :
Abousleman, Glen P. ; Lam, Tuyet-Trang ; Karam, Lina J.
Author_Institution :
Compression Commun. & Intelligence Lab., Gen. Dynamics Decision Syst., Scottsdale, AZ, USA
fDate :
4/1/2002 12:00:00 AM
Abstract :
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
Keywords :
data compression; geophysical signal processing; geophysical techniques; image coding; multidimensional signal processing; quantisation (signal); remote sensing; terrain mapping; trellis coded modulation; trellis codes; binary symmetric channel; channel optimized; data compression; geophysical measurement technique; hyperspectral remote sensing; image coding; image compression; land surface; multispectral remote sensing; optical method; remote sensing; robust method; terrain mapping; trellis coded quantization; wavelet-based image coder; Channel coding; Decoding; Design optimization; Hyperspectral imaging; Image coding; Noise robustness; Protection; Quantization; Security; Streaming media;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2002.1006360