Title :
Hyperspectral Image Compression Employing a Model of Anomalous Pixels
Author :
Penna, Barbara ; Tillo, Tammam ; Magli, Enrico ; Olmo, Gabriella
Author_Institution :
Politecnico di Torino, Turino
Abstract :
We propose a new lossy compression algorithm for hyperspectral images, which is 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 Airborne Visible/Infrared Imaging Spectrometer 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.
Keywords :
Karhunen-Loeve transforms; data compression; geophysical techniques; image coding; Airborne Visible-Infrared Imaging Spectrometer; anomalous pixels model; anomaly detection performance; hyperspectral images; lossy compression algorithm; rate-distortion performance; spatial JPEG 2000; spectral Karhunen-Loeve transform; Compression algorithms; Hyperspectral imaging; Image coding; Infrared imaging; Infrared spectra; Karhunen-Loeve transforms; Layout; Pixel; Spectroscopy; Transform coding; Anomaly detection; JPEG 2000; Karhunen–LoÈve transform (KLT); Reed–Xiaoli (RX) algorithm; discrete wavelet transform (DWT); hyperspectral data; lossy compression; wavelet;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2007.903976
