Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data

Naoufal Amrani, Joan Serra-Sagrista, Miguel Hernandez-Cabronero, Michael W Marcellin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Regression Wavelet Analysis (RWA) is a novel wavelet-based scheme for coding hyperspectral images that employs multiple regression analysis to exploit the relationships among spectral wavelet-transformed components. The scheme is based on a pyramidal prediction, using different regression models, to increase the statistical independence in the wavelet domain. For lossless coding, RWA has proven to be superior to other spectral transform like PCA and to the best and most recent coding standard in remote sensing, CCSDS-123.0. In this paper we show that RWA also allows progressive lossy-to-lossless (PLL) coding and that it attains a rate-distortion performance superior to those obtained with state-of-the-art schemes. To take into account the predictive significance of the spectral components, we propose a Prediction Weighting scheme for JPEG2000 that captures the contribution of each transformed component to the prediction process.

Original languageEnglish (US)
Title of host publicationProceedings - DCC 2016: 2016 Data Compression Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-130
Number of pages10
ISBN (Electronic)9781509018536
DOIs
StatePublished - Dec 15 2016
Event2016 Data Compression Conference, DCC 2016 - Snowbird, United States
Duration: Mar 29 2016Apr 1 2016

Other

Other2016 Data Compression Conference, DCC 2016
CountryUnited States
CitySnowbird
Period3/29/164/1/16

Fingerprint

Wavelet analysis
Remote sensing
Regression analysis

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Amrani, N., Serra-Sagrista, J., Hernandez-Cabronero, M., & Marcellin, M. W. (2016). Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data. In Proceedings - DCC 2016: 2016 Data Compression Conference (pp. 121-130). [7786156] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCC.2016.43

Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data. / Amrani, Naoufal; Serra-Sagrista, Joan; Hernandez-Cabronero, Miguel; Marcellin, Michael W.

Proceedings - DCC 2016: 2016 Data Compression Conference. Institute of Electrical and Electronics Engineers Inc., 2016. p. 121-130 7786156.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Amrani, N, Serra-Sagrista, J, Hernandez-Cabronero, M & Marcellin, MW 2016, Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data. in Proceedings - DCC 2016: 2016 Data Compression Conference., 7786156, Institute of Electrical and Electronics Engineers Inc., pp. 121-130, 2016 Data Compression Conference, DCC 2016, Snowbird, United States, 3/29/16. https://doi.org/10.1109/DCC.2016.43
Amrani N, Serra-Sagrista J, Hernandez-Cabronero M, Marcellin MW. Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data. In Proceedings - DCC 2016: 2016 Data Compression Conference. Institute of Electrical and Electronics Engineers Inc. 2016. p. 121-130. 7786156 https://doi.org/10.1109/DCC.2016.43
Amrani, Naoufal ; Serra-Sagrista, Joan ; Hernandez-Cabronero, Miguel ; Marcellin, Michael W. / Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data. Proceedings - DCC 2016: 2016 Data Compression Conference. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 121-130
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