Paper
15 November 2007 Adaptive image fusion based on nonsubsampled contourlet transform
Author Affiliations +
Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678629 (2007) https://doi.org/10.1117/12.749591
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Multiresolution-based image fusion has been the focus of considerable research attention in recent years with a number of algorithms proposed. In most of the algorithms, however, the parameter configuration is usually based on experience. This paper proposes an adaptive image fusion algorithm based on the nonsubsampled contourlet transform (NSCT), which realizes automatic parameter adjustment and gets rid of the adverse effect caused by artificial factors. The algorithm incorporates the quality metric of structural similarity (SSIM) into the NSCT fusion framework. The SSIM value is calculated to assess the fused image quality, and then it is fed back to the fusion algorithm to achieve a better fusion by directing parameters (level of decomposition and flag of decomposition direction) adjustment. Based on the cross entropy, the local cross entropy (LCE) is constructed and used to determine an optimal choice of information source for the fused coefficients at each scale and direction. Experimental results show that the proposed method achieves the best fusion compared to three other methods judged on both the objective metrics and visual inspection and exhibits robust against varying noises.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiongmei Zhang, Junshan Li, Zhaoxiang Yi, and Wei Yang "Adaptive image fusion based on nonsubsampled contourlet transform", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678629 (15 November 2007); https://doi.org/10.1117/12.749591
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Cited by 2 scholarly publications.
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KEYWORDS
Image fusion

Image quality

Discrete wavelet transforms

Image processing

Wavelets

Optical inspection

Algorithm development

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