Title :
Multispectral image compression using eigen-region-based segmentation
Author :
Chang, Lena ; Cheng, Ching-Min
Author_Institution :
Dept. of Merchant Marine, Nat. Taiwan Ocean Univ., China
Abstract :
In the study, we present an effective segmentation technique for multispectral image compression. This technique fully exploits the spectral and spatial correlation in the data. The original image is first divided into some proper eigen-regions according to the local terrain characteristics of the image. Then, each region image is transformed by the corresponding KL transformation function and results in an eigen-region image for further compression. Simulation tests performed on Landsat TM images have demonstrated that the proposed compression scheme is suitable for multispectral image
Keywords :
Karhunen-Loeve transforms; data compression; eigenvalues and eigenfunctions; geophysical signal processing; image coding; image segmentation; remote sensing; KL transformation function; Landsat TM images; eigenregion-based segmentation; local terrain characteristics; multispectral image compression; spatial correlation; spectral correlation; Covariance matrix; Decorrelation; Image coding; Image segmentation; Karhunen-Loeve transforms; Multispectral imaging; Oceans; Satellites; Software libraries; Symmetric matrices;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
DOI :
10.1109/IGARSS.2001.977091
