Anomaly-Based Hyperspectral Image Compression

Author

Du, Qian ; Zhu, Wei ; Fowler, James E.

Author_Institution

Dept. of Electr. & Comput. Eng., Mississippi State Univ., Starkville, MS

Volume

2

fYear

2008

fDate

7-11 July 2008

Abstract

We propose a new lossy compression algorithm for hyperspectral images, which is based on spectral principal component analysis (PCA), followed by JPEG2000 (JP2K). The approach employs an anomaly-removal model in the compression process to preserve anomalous pixels. Results on two different hyperspectral image scenes show that the new algorithm not only provides good post-compression anomaly-detection performance but also improves rate-distortion performance.

Keywords

discrete wavelet transforms; geophysical techniques; principal component analysis; remote sensing; AA algorithm; DWT; JPEG2000; PCA; anomalous pixel preservation; anomaly-adjusted algorithm; anomaly-removal model; discrete wavelet transform; hyperspectral image; image compression process; lossy compression algorithm; post-compression anomaly-detection; principal component analysis; rate-distortion performance; Compression algorithms; Decorrelation; Discrete wavelet transforms; Hyperspectral imaging; Image coding; Personal communication networks; Pixel; Principal component analysis; Rate-distortion; Transform coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4779159

Filename

4779159