Compression of hyper-spectral images based on quadtree partitioning

Author

Wei Zhang ; Ming Dai ; Chuan-li Yin

Author_Institution

Grad. Univ., Chinese Acad. of Sci., Beijing, China

fYear

2009

fDate

8-11 Aug. 2009

Firstpage

421

Lastpage

423

Abstract

The paper analyzes the characteristic features of hyper-spectral image and presents a compression of hyper-spectral images based on quadtree partitioning. Quadtree partition is used to get the mean image of the whole image and the significant correlation of image can be decorrelated by subtract the mean image from original image. The difference image is compressed by DCT and encoded with arithmetic code. Experiment show the algorithm is simple and easy to use in real-time image compressing.

Keywords

arithmetic codes; correlation methods; data compression; discrete cosine transforms; image coding; quadtrees; spectral analysis; DCT; arithmetic code; discrete cosine transform; encoding; hyper-spectral image compression; mean image; quadtree partitioning; significant correlation method; Decorrelation; Frequency; Hyperspectral sensors; Image analysis; Image coding; Optical computing; Optical sensors; Physics computing; Pixel; Spatial resolution; Hyper-Spectral Image; Image Compression; quadtree partition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-4519-6

Electronic_ISBN

978-1-4244-4520-2

Type

conf

DOI

10.1109/ICCSIT.2009.5234533

Filename

5234533