Infrared and visible image fusion based on NSCT and fuzzy logic

A novel infrared (IR) and visible image fusion method based on nonsubsampled contourlet transform (NSCT) and fuzzy logic is proposed. Input IR and visible images are decomposed into a series of low frequency and high frequency subbands by using NSCT. The degree of membership to the background and the target for each pixel in the low frequency subband of the IR image is determined by using fuzzy logic. An adaptive weighted average is then taken as the fusion of low frequency subband coefficients while maximum absolution selection is performed for the fusion of high frequency subband coefficients. The fused image is obtained by taking inverse NSCT of the fused coefficients. Experimental results with real IR and visible images show that the proposed method effectively enhances infrared targets and preserves details of the visible image.

[1]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[2]  Alessandro Saffiotti,et al.  The uses of fuzzy logic in autonomous robot navigation , 1997, Soft Comput..

[3]  Rick S. Blum,et al.  A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application , 1999, Proc. IEEE.

[4]  M. Farooq,et al.  A real time pixel-level based image fusion via adaptive weight averaging , 2000, Proceedings of the Third International Conference on Information Fusion.

[5]  G. Qu,et al.  Information measure for performance of image fusion , 2002 .

[6]  Gemma Piella,et al.  A general framework for multiresolution image fusion: from pixels to regions , 2003, Inf. Fusion.

[7]  Yufeng Zheng,et al.  An advanced image fusion algorithm based on wavelet transform: incorporation with PCA and morphological processing , 2004, IS&T/SPIE Electronic Imaging.

[8]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[9]  Minh N. Do,et al.  The Nonsubsampled Contourlet Transform: Theory, Design, and Applications , 2006, IEEE Transactions on Image Processing.

[10]  Yang Xu,et al.  Fuzzy logic from the viewpoint of machine intelligence , 2006, Fuzzy Sets Syst..

[11]  Joel Lanir,et al.  Comparing Multispectral Image Fusion Methods for a Target Detection Task , 2006, 2006 9th International Conference on Information Fusion.

[12]  Miao Qiguang Fusion algorithm of infrared and visible light images based on NSCT transform , 2008 .

[13]  Guofan Jin,et al.  One color contrast enhanced infrared and visible image fusion method , 2010 .