Title :
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
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;
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
DOI :
10.1109/IGARSS.2008.4779159
