We propose a new lossy compression algorithm for hyperspectral images, based on the spectral Karhunen-Loeve transform followed by spatial JPEG 2000, which employs a model of anomalous pixels during the compression process. Results on AVIRIS scenes show that the new algorithm provides better rate-distortion performance, as well as improved anomaly detection performance, with respect to the state-of-the-art.

Hyperspectral Image Compression Employing a Model of Anomalous Pixels / Penna, Barbara; Tillo, Tammam; Magli, Enrico; Olmo, Gabriella. - In: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS. - ISSN 1545-598X. - STAMPA. - 4:4(2007), pp. 664-668. [10.1109/LGRS.2007.903976]

Hyperspectral Image Compression Employing a Model of Anomalous Pixels

PENNA, BARBARA;TILLO, TAMMAM;MAGLI, ENRICO;OLMO, Gabriella
2007

Abstract

We propose a new lossy compression algorithm for hyperspectral images, based on the spectral Karhunen-Loeve transform followed by spatial JPEG 2000, which employs a model of anomalous pixels during the compression process. Results on AVIRIS scenes show that the new algorithm provides better rate-distortion performance, as well as improved anomaly detection performance, with respect to the state-of-the-art.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1642351
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