Title :
Multi-spectral remote sensing images fusion based on k-th central moment
Author :
Yao, Xueheng ; Xie, Lihua ; Huang, Dengshan
Author_Institution :
Dept. of Geomatics, Central South Univ., Changsha, China
Abstract :
With the remote sense technologies applied into more and more fields, the existing methods of remote sense data fusion, like HSV, PCA, HIS transform, can not meet the demands of all kinds of situations occurring in different fields. This paper presents a new method of Multi-spectral remote sensing images information fusion in order to provide more choices for people. The new method based on k-th central moment can be used to reconstruct a series of images based on the difference between feature vectors and mean vectors of all bands. Comparing with grey image of every band, the reconstructing images´ quantity of information improved greatly as k value is low. With k increased, the reconstructing images´ quantity of information decreased sharply and the difference between feature vectors and mean vectors was amplified. This method can be as a tool to detect the piece of special regions which are different from around environment, like forest fire, environmental pollution, insect pest, flood monitoring, etc.
Keywords :
geophysical image processing; geophysical techniques; image fusion; image reconstruction; remote sensing; environmental pollution; feature vectors; flood monitoring; forest fire; grey image; image reconstruction; insect pest; k-th central moment; mean vectors; multispectral remote sensing image fusion; remote sensing data fusion; Data mining; Entropy; Histograms; Image fusion; Image reconstruction; Principal component analysis; Remote sensing; difference of images; image fusion; k central moment; vectors space;
Conference_Titel :
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-8514-7
DOI :
10.1109/IITA-GRS.2010.5603391