Title :
A novel scheme for the compression and classification of hyperspectral images
Author :
Xie, Bei ; Bose, Tarnal ; Merényi, Erzsébet
Author_Institution :
Bradley Dept. of Electr. & Comput. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Abstract :
Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data at the receiver. The advantage of this scheme is that fewer computations are needed. Computer simulations are performed on hyperspectral imagery.
Keywords :
data compression; geophysical signal processing; image classification; image coding; quantisation (signal); remote sensing; transforms; computer simulations; hyperspectral image classification; hyperspectral image compression; hyperspectral image decompression; image quantization; image transform; Artificial neural networks; Compression algorithms; Discrete cosine transforms; Discrete transforms; Hyperspectral imaging; Hyperspectral sensors; Image classification; Image coding; Pulse modulation; Quantization; Hyperspectral imagery; image classification; lossy data compression; neural network;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS '09. First Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4686-5
Electronic_ISBN :
978-1-4244-4687-2
DOI :
10.1109/WHISPERS.2009.5289075