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

fYear

2009

fDate

26-28 Aug. 2009

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/WHISPERS.2009.5289075

Filename

5289075