Special Section on Advances in Onboard Payload Data Compression

Predictor analysis for onboard lossy predictive compression of multispectral and hyperspectral images

[+] Author Affiliations
Marco Ricci

Politecnico di Torino, Dipartimento di Elettronica e Telecomunicazioni, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy

Enrico Magli

Politecnico di Torino, Dipartimento di Elettronica e Telecomunicazioni, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy

J. Appl. Remote Sens. 7(1), 074591 (Aug 09, 2013). doi:10.1117/1.JRS.7.074591
History: Received January 31, 2013; Revised June 27, 2013; Accepted July 11, 2013
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Abstract.  The predictive lossy compression paradigm, which is emerging as an interesting alternative to conventional transform coding techniques, is studied. We first discuss this paradigm and outline the advantages and drawbacks with respect to transform coding. Next, we consider two low-complexity predictors and compare them under equal conditions on a large set of multispectral and hyperspectral images. Besides their rate-distortion performance, we attempt to gain some insight on the “quality” of the prediction residuals, comparing bit-rate and variance, and calculating the kurtosis. The results allow us to outline the directions for improvement of the algorithms, mainly in the treatment of noisy channels and the use of appropriate statistical models for the entropy-coding stage.

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© 2013 Society of Photo-Optical Instrumentation Engineers

Citation

Marco Ricci and Enrico Magli
"Predictor analysis for onboard lossy predictive compression of multispectral and hyperspectral images", J. Appl. Remote Sens. 7(1), 074591 (Aug 09, 2013). ; http://dx.doi.org/10.1117/1.JRS.7.074591


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