Detail preserved fusion of infrared and visual images by using opening and closing based toggle operator

Abstract Image fusion is an effective way to combine the useful information in infrared and visual images. One crucial part of infrared and visual image fusion is extracting the useful image features of the original images, and thus maintaining the image details in the final fusion image well. In this paper, a detail preserving algorithm for infrared and visual image fusion based on the multi-scale toggle operator which uses morphological opening and closing operators as primitives is proposed. The toggle operator using opening and closing as primitives is discussed. Also, extracting image regions using the constructed toggle operator is demonstrated. Then, based on the multi-scale theory, extraction of multi-scale image regions using the constructed toggle operator is demonstrated. After appropriately utilizing the extracted multi-scale image features, the effective fusion result is obtained through the strategy of contrast enlargement. Experimental results show that, because the toggle operator using opening and closing as primitives could extract image features well in the original infrared and visual images, the proposed algorithm performs well for detail preserved fusion of infrared and visual images.

[1]  Jason Jianjun Gu,et al.  Multi-focus image fusion using PCNN , 2010, Pattern Recognit..

[2]  Yun Zhang,et al.  Wavelet based image fusion techniques — An introduction, review and comparison , 2007 .

[3]  Vladimir S. Petrovic,et al.  Gradient-based multiresolution image fusion , 2004, IEEE Transactions on Image Processing.

[4]  Veysel Aslantas,et al.  A comparison of criterion functions for fusion of multi-focus noisy images , 2009 .

[5]  J. Wesley Roberts,et al.  Assessment of image fusion procedures using entropy, image quality, and multispectral classification , 2008 .

[6]  David Bull,et al.  Region-Based Multimodal Image Fusion Using ICA Bases , 2007 .

[7]  Xiangzhi Bai,et al.  Edge preserved image fusion based on multiscale toggle contrast operator , 2011, Image Vis. Comput..

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

[9]  Luciano Alparone,et al.  Remote sensing image fusion using the curvelet transform , 2007, Inf. Fusion.

[10]  Bhabatosh Chanda,et al.  Fusion of 2D grayscale images using multiscale morphology , 2001, Pattern Recognit..

[11]  Rick S. Blum,et al.  Theoretical analysis of an information-based quality measure for image fusion , 2008, Inf. Fusion.

[12]  X. BAI.  Morphological enhancement of microscopy mineral image using opening‐ and closing‐based toggle operator , 2014, Journal of microscopy.

[13]  Xiangzhi Bai,et al.  Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform. , 2011, Optics express.

[14]  Gonzalo Pajares,et al.  A wavelet-based image fusion tutorial , 2004, Pattern Recognit..

[15]  Mohamed A. Deriche,et al.  Scale-Space Properties of the Multiscale Morphological Dilation-Erosion , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Alexander Toet,et al.  Towards cognitive image fusion , 2010, Inf. Fusion.

[17]  Rafael García,et al.  Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition , 2004, IEEE Transactions on Geoscience and Remote Sensing.