Lossy Hyperspectral Images Coding with Exogenous Quasi Optimal Transforms
| Autor: | Michel Barret, Jean-Louis Gutzwiller, Florio Dalla Vedova, Isidore Paul Akam Bita |
|---|---|
| Přispěvatelé: | SUPELEC-Campus Metz, Ecole Supérieure d'Electricité - SUPELEC (FRANCE), LUXSPACESarl, LUXSPACE Sarl |
| Rok vydání: | 2009 |
| Předmět: |
Karhunen–Loève theorem
Linear transform Transform Coding business.industry 0211 other engineering and technologies Hyperspectral imaging 020206 networking & telecommunications Pattern recognition 02 engineering and technology computer.file_format Lossy compression [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing JPEG 2000 0202 electrical engineering electronic engineering information engineering Codec Artificial intelligence Hyperspectral Image Compression business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing computer Transform coding 021101 geological & geomatics engineering Mathematics Coding (social sciences) |
| Zdroj: | DCC Proceedings of Data Compression Conference DCC 2009 DCC 2009, Mar 2009, Snowbird, Utah, United States. pp.411-419, ⟨10.1109/DCC.2009.8⟩ |
| DOI: | 10.1109/dcc.2009.8 |
| Popis: | International audience; It is well known in transform coding that the Karhunen-Loève Transform (KLT) can be suboptimal for non Gaussian sources. However in many applications using JPEG2000 Part 2 codecs, the KLT is generally considered as the optimal linear transform for reducing redundancies between components of hyperspectral images. In previous works, optimal spectral transforms (OST) compatible with the JPEG2000 Part 2 standard have been introduced, performing better than the KLT but with an heavier computational cost. In this paper, we show that the OST computed on a learning basis constituted of Hyperion hyperspectral images issued from one sensor performs very well, and even better than the KLT, on other images issued from the same sensor. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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