DocumentCode :
2395775
Title :
Self-adaptive image fusion based on multi-resolution decomposition using wavelet packet analysis
Author :
Chai, Yan-mei ; Zhao, Rong-chun ; Ren, Jin-Chang
Author_Institution :
Sch. of Comput., Northwestern Polytech. Univ., Xi´´an, China
Volume :
7
fYear :
2004
fDate :
26-29 Aug. 2004
Firstpage :
4049
Abstract :
A self-adaptive image fusion method using multi-resolution analysis is proposed, in which multi-spectral (TM) and SAR images are fused. Firstly, we convert TM images from RGB to IHS colour space. Then, the I component in TM images are fused with SAR images using quadtree decomposition of images by wavelet packet analysis. The final results are obtained through inverse wavelet and IHS transforms, respectively. The highlight of our method is regional edge intensity (REI) based self-adaptive fusion. Experimental results demonstrate that better performance can be obtained from our method in improving definitions and correlations compared with original TM and SAR images.
Keywords :
correlation methods; image colour analysis; image resolution; quadtrees; radar imaging; sensor fusion; synthetic aperture radar; wavelet transforms; RGB colour space; SAR images; correlation methods; image quadtree decomposition; intensity hue saturation colour space; intensity hue saturation transforms; inverse wavelet transform; multiresolution analysis; multiresolution decomposition; multispectral images; regional edge intensity; self adaptive image fusion; wavelet packet analysis; Data mining; Image analysis; Image converters; Image fusion; Image resolution; Remote monitoring; Spatial resolution; Wavelet analysis; Wavelet packets; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
Type :
conf
DOI :
10.1109/ICMLC.2004.1384547
Filename :
1384547
Link To Document :
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