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Proceedings Paper

A multi-sensor image fusion algorithm based on region-based selection and IHS transform
Author(s): Xinnan Fan; Ji Zhang; Min Li; Pengfei Shi; Bingbin Zheng; Xuewu Zhang; Zhixiang Yang
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Paper Abstract

The multi-sensor image fusion technology can obtain a more comprehensive and more accurate and reliable image, in order to understand the scene or recognize the target more easily. However, most existing algorithms are mainly based on optical remote sensing images, which is highly susceptible by media interference, supplemented by SAR images. The image fusion between SAR images and PAN images also cannot save the textural feature and the color information effectively at the same time. In view of these problems, this paper presents a multi-sensor image fusion algorithm based on region-based selection and IHS transform. The SAR image and PAN image are firstly IHS transformed to achieve the intensity (I), hue (H) and saturation (S) weights. The I weights of SAR image and PAN image are separately decomposed using SIDWT algorithm to extract wavelet coefficients. Then, the I weight of SAR image is divided into regular area and irregular area based on a new adaptive segmentation method. A new fusion rules is presented according to local feature, and then used to fuse corresponding wavelet coefficients of the I weight of SAR image and PAN image. Inverse SIDWT is carried out on the fused wavelet coefficients to get the I weight (I’) of fused image. Finally, the fused image is obtained by inverse IHS transform of I’ weight with the H, S weight of PAN image. Experimental results of real images validated the effectiveness of the proposed algorithm by objective evaluation such as standard deviation, entropy, average gradient, etc.

Paper Details

Date Published: 24 November 2014
PDF: 6 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012Y (24 November 2014); doi: 10.1117/12.2073105
Show Author Affiliations
Xinnan Fan, Hohai Univ. (China)
Ji Zhang, Hohai Univ. (China)
Min Li, Hohai Univ. (China)
Pengfei Shi, Hohai Univ. (China)
Bingbin Zheng, Hohai Univ. (China)
Xuewu Zhang, Hohai Univ. (China)
Zhixiang Yang, Water Planning and Designing Institute (China)


Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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