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Página principal > Artículos > Artículos publicados > Regression Wavelet Analysis for Near-Lossless Remote Sensing Data Compression |
Fecha: | 2020 |
Resumen: | Regression wavelet analysis (RWA) is one of the current state-of-the-art lossless compression techniques for remote sensing data. This article presents the first regression-based near-lossless compression method. It is built upon RWA, a quantizer, and a feedback loop to compensate the quantization error. Our near-lossless RWA (NLRWA) proposal can be followed by any entropy coding technique. Here, the NLRWA is coupled with a bitplane-based coder that supports progressive decoding. This successfully enables gradual quality refinement and lossless and near-lossless recovery. A smart strategy for selecting the NLRWA quantization steps is also included. Experimental results show that the proposed scheme outperforms the state-of-the-art lossless and the near-lossless compression methods in terms of compression ratios and quality retrieval. |
Ayudas: | Ministerio de Economía y Competitividad RTI2018-095287-B-I00 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-463 |
Nota: | Altres ajuts: Universitat Autònoma de Barcelona under Grant UAB-PIF-472/2015 |
Derechos: | Tots els drets reservats. |
Lengua: | Anglès |
Documento: | Article ; recerca ; Versió acceptada per publicar |
Materia: | Lossless and near-lossless compression ; Pyramidal multiresolution scheme ; Regression wavelet analysis ; Remote sensing data compression |
Publicado en: | IEEE transactions on geoscience and remote sensing, Vol. 58, Issue 2 (February 2020) , p. 790-798, ISSN 1558-0644 |
Postprint 10 p, 801.8 KB |