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Technique for image fusion based on non-subsampled contourlet transform domain improved NMF

Science China(Information Sciences) 2010年第12期53卷 2429-2440页

作者： KONG WeiWei1,LEI YingJie1,LEI Yang1 & ZHANG Jie2 1Department of Computer Engineering,Missile Institute,Air Force Engineering University,Xi'an 713800,China 2Department of Computer,Qinghai University,Xining 810016,China Department of Computer Engineering Missile Institute Air Force Engineering University Xi’an China Department of Computer Qinghai University Xining China

To overcome the problem of multi-sensor image fusion,a technique for image fusion based on non-subsampled contourlet transform(NSCT) domain improved nonnegative matrix factorization(NMF) is ***,by using NSCT,multi-scale and multi-direction sparse decompositions of source images are ***,an improved NMF technique is utilized to complete the fusion of low-frequency *** low-frequency fused image can be produced fast by the process which does not involve the randomization of the vectors W and H at all,in addition,the fusion course of high-frequency sub-images can be dealt with by use of the model of adaptive unit-fast-linking pulse coupled neural network(AUFLPCNN).Finally,the ultimate fused image can be obtained by synthesizing all sub-images with inverse *** simulated experiments show that the technique is effective.

关键词： image fusion non-subsampled contourlet transform nonnegative matrix factorization singular value decomposition

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Deformable Registration Algorithm via non-subsampled contourlet transform and Saliency Map

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Journal of Shanghai Jiaotong university(Science) 2022年第4期27卷 452-462页

作者： Chang Qing Yang Wenyou Chen Lanlan School of Information Science and Engineering East China University of Science and TechnologyShanghai200237China

Medical image registration is widely used in image-guided therapy and image-guided surgery to estimate spatial correspondence between planning and treatment ***,most methods based on intensity have the problems of matching ambiguity and ignoring the influence of weak correspondence areas on the overall *** this study,we propose a novel general-purpose registration algorithm based on free-form deformation by non-subsampled contourlet transform and saliency map,which can reduce the matching ambiguities and maintain the topological structure of weak correspondence *** optimization method based on Markov random fields is used to optimize the registration *** on four public datasets from brain,cardiac,and lung have demonstrated the general applicability and the accuracy of our algorithm compared with two state-of-the-art methods.

关键词： medical image registration non-subsampled contourlet transform saliency map Markov random fields

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Image edge detection based on pulse coupled neural network and modulus maxima in non-subsampled contourlet domain

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The Journal of China Universities of Posts and Telecommunications 2018年第3期25卷 55-64页

作者： Hu Ling Chang Xia Qian Wei School of Mathematics and Information Science North Minzu University

Edge is the intrinsic geometric structure of an image. Edge detection methods are the key technologies in the lleld of image processing. In this paper, a multi-scale image edge detection method is proposed to effectively extract image geometric features. A source image is decomposed into the high frequency directional sub-bands coefficients and the low frequency sub-bands coefficients by non-subampled contourlet transform （NSCT）. The high frequency sub-bands coefficients are used to detect the abundant details of the image edges by the modulus maxima （MM） algorithm. The low frequency sub-band coefficients are used to detect the basic contour line of the image edges by the pulse coupled neural network （PCNN）. The final edge detection image is reconstructed with detected edge information at different scales and different directional sub-bands in the NSCT domain. Experimental results demonstrate that the proposed method outperforms several state-of-art image edge detection methods in both visual effects and objective evaluation.

关键词： edge detection modulus maxima pulse coupled neural network wavelet transform non-subsampled contourlet transform

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Fusion of Infrared and Visible Light Images Based on Region Segmentation

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Chinese Journal of Aeronautics 2009年第1期22卷 75-80页

作者：刘坤郭雷李晖晖陈敬松西北工业大学自动化学院中国航空无线电电子研究所

This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. The non-subsampled contourlet transform (NSCT) provides a flexible multiresolution,local and directional image expansion,and also a sparse representation for two-dimensional (2-D) piecewise smooth signal building images,and then different fusion rules are applied to fuse the NSCT coefficients fo...

关键词： image processing image fusion non-subsampled contourlet transform region segmentation infrared imaging

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