Hyperspectral Image Compression Employing a Model of Anomalous Pixels

Author

Penna, Barbara ; Tillo, Tammam ; Magli, Enrico ; Olmo, Gabriella

Author_Institution

Politecnico di Torino, Turino

Volume

4

Issue

4

fYear

2007

Firstpage

664

Lastpage

668

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;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2007.903976

Filename

4317542