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Proceedings Paper

Image fusion using lifting wavelet transform with human visual features
Author(s): Xiaobo Gu; Zhenming Peng; Zhiwei Chen; Lin Yuan; Bingquan Huang
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Paper Abstract

We focus on the method of image registration and fusion and introduce all kinds of existing registration and fusion algorithm based on lifting wavelet in detail in this paper. Based on the characteristics of the infrared and visible images, this paper presents a registration approach using lifting wavelet transform to extract edge feature points, and improve the fusion algorithm based on features of human vision system (HVS). The methods refer much other knowledge such as lifting scheme, edge detection, affine transformation, HVS and fusion rules. A fast multi-resolution image fusion method based on visual features for infrared and visible images is proposed in this paper. The source images are decomposed using CDF9/7 lifting wavelet transform, respectively. Then it calculated the visual features of each sub-image and chose the different rule of fusion based on visual features. Finally, a fused image is reconstructed by using inverse lifting wavelet transform. Experimental results demonstrate that the proposed method has apparent advantage in information preservation and resolution even if the source images have low signal to noise ratio (SNR), and the algorithm is more effective in computational speed.

Paper Details

Date Published: 10 November 2010
PDF: 7 pages
Proc. SPIE 7850, Optoelectronic Imaging and Multimedia Technology, 78502L (10 November 2010); doi: 10.1117/12.871546
Show Author Affiliations
Xiaobo Gu, Univ. of Electronic Science and Technology of China (China)
Zhenming Peng, Univ. of Electronic Science and Technology of China (China)
Zhiwei Chen, Univ. of Electronic Science and Technology of China (China)
Lin Yuan, Univ. of Electronic Science and Technology of China (China)
Bingquan Huang, Univ. of Electronic Science and Technology of China (China)

Published in SPIE Proceedings Vol. 7850:
Optoelectronic Imaging and Multimedia Technology
Toru Yoshizawa; Ping Wei; Jesse Zheng; Tsutomu Shimura, Editor(s)

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