Lossy Hyperspectral Images Coding with Exogenous Quasi Optimal Transforms

Michel Barret (1) , Isidore Paul Akam Bita (2) , Jean-Louis Gutzwiller (1) , Florio Dalla Vedova (2)

1 SUPELEC-Campus Metz
2 LUXSPACESarl

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.

Mots clés: Hyperspectral Image Compression; Transform Coding

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Michel Barret, Isidore Paul Akam Bita, Jean-Louis Gutzwiller, Florio Dalla Vedova. Lossy Hyperspectral Images Coding with Exogenous Quasi Optimal Transforms. DCC 2009, Mar 2009, Snowbird, Utah, United States. pp.411-419, ⟨10.1109/DCC.2009.8⟩. ⟨hal-00396967⟩