Title :
Signal Processing for Hyperspectral Data
Author :
Varshney, Pramod K. ; Arora, Mukesh Kumar ; Rao, Raghuveer M.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY
Abstract :
Hyperspectral data form a data-cube consisting of images of an object collected at several hundred, closely spaced wavelengths. They have been found to be of significant potential benefit in areas such as remote sensing of the Earth, medicine, and non-destructive evaluation. Effective extraction of information from the hyperspectral data cube presents several signal processing challenges, some of them unique to hyperspectral data. The problems involved range from registration and enhancement to development of statistical signal processing algorithms and models for object detection and classification. The focus of this paper is to provide an overview of select processing and modeling techniques for hyperspectral data
Keywords :
geophysical signal processing; image classification; image enhancement; image registration; object detection; remote sensing; statistical analysis; data-cube consisting; hyperspectral data; object classification; object detection; remote sensing; signal enhancement; signal processing; signal registration; statistical signal processing algorithms; Biomedical imaging; Biomedical signal processing; Data mining; Earth; Hyperspectral imaging; Hyperspectral sensors; Object detection; Remote sensing; Signal processing; Signal processing algorithms;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1661492