Image fusion using lifting wavelet transform with human visual features

Xiaobo Gu; Zhenming Peng; Zhiwei Chen; Lin Yuan; Bingquan Huang

doi:10.1117/12.871546

10 November 2010 Image fusion using lifting wavelet transform with human visual features

Xiaobo Gu, Zhenming Peng, Zhiwei Chen, Lin Yuan, Bingquan Huang

Proceedings Volume 7850, Optoelectronic Imaging and Multimedia Technology; 78502L (2010) https://doi.org/10.1117/12.871546
Event: Photonics Asia 2010, 2010, Beijing, China

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.

Citation Download Citation

Xiaobo Gu, Zhenming Peng, Zhiwei Chen, Lin Yuan, and Bingquan Huang "Image fusion using lifting wavelet transform with human visual features", Proc. SPIE 7850, Optoelectronic Imaging and Multimedia Technology, 78502L (10 November 2010); https://doi.org/10.1117/12.871546

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KEYWORDS

Image fusion

Visualization

Wavelet transforms

Wavelets

Infrared imaging

Detection and tracking algorithms

Infrared radiation

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