Cost and scalability improvements to the Karhunen-Loéve transform for remote-sensing image coding
Blanes Garcia, Ian (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)

Fecha:	2010
Resumen:	The Karhunen-Loêve transform (KLT) is widely used in hyperspectral image compression because of its high spectral decorrelation properties. However, its use entails a very high computational cost. To overcome this computational cost and to increase its scalability, in this paper, we introduce a multilevel clustering approach for the KLT. As the set of different multilevel clustering structures is very large, a two-stage process is used to carefully pick the best members for each specific situation. First, several candidate structures are generated through local search and eigenthresholding methods, and then, candidates are further screened to select the best clustering configuration. Two multilevel clustering combinations are proposed for hyperspectral image compression: one with the coding performance of the KLT but with much lower computational requirements and increased scalability and another one that outperforms a lossy wavelet transform, as spectral decorrelator, in quality, cost, and scalability. Extensive experimental validation is performed, with images from both the AVIRIS and Hyperion sets, and with JPEG2000, 3D-TCE, and CCSDS-Image Data Compression recommendation as image coders. Experiments also include classification-based results produced by k-means clustering and Reed-Xiaoli anomaly detection.
Ayudas:	Ministerio de Ciencia e Innovación TIN2009-14426-C02-01 Ministerio de Ciencia e Innovación TIN2009-05737-E Agència de Gestió d'Ajuts Universitaris i de Recerca 2009/SGR-1224
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Lengua:	Anglès
Documento:	Article ; recerca ; Versió acceptada per publicar
Materia:	Component scalability ; Hyperspectral data coding ; Karhunen-Loêve Transform (KLT) ; Low cost ; Progressive lossy-to-lossless (PLL) ; Lossy compression
Publicado en:	IEEE transactions on geoscience and remote sensing, Vol. 48, no. 7 (July 2010) , p. 2854-2863, ISSN 1558-0644

DOI: 10.1109/TGRS.2010.2042063

Postprint 11 p, 1.0 MB

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