Title :
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
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;
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
DOI :
10.1109/ICCSIT.2009.5234533
