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Research On Image Fusion Based On Nonsubsameplcd Contourlet Transform

Posted on:2013-01-07Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y T YangFull Text:PDF
GTID:1118330371998869Subject:Mechanical and electrical engineering
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The multi-source image fusion technique take the image as the object of study inthe information fusion field, one of the most important branches of the Multi-sourceinformation fusion-Visual Information Fusion. It s a mordern high-tech combinedsensor theory, analog to digital signal conversion, digital image processing, computervision, artificial intelligence and many other disciplines, has been widely used inmany range of areas such as military and civilian applications. In recent years, themulti-resolution decomposition based on transform domain pixel-level image fusionalgorithms have widely used in the field of multi-source image fusion, effectivelyovercomed the spatial spectrum distortion and have obtained the better effect.In this dissertation, on the basis of the previous pixel-level multi-source imagefusion algorithms research, in the field of multi-scale image fusion, we found that thewidely used method which called wavelet transform has some limitations. It cannoteffectively represent the most prominent visual effects such as the line discontinuities and the curve discontinuities in the two-dimensional image, and onlyuse the singular points to approximate the singular lines or curved surfaces. Thislimitation resulted in the mistiness of the profile and texture in the image. Therefore,aim at the wavelet s limitations, the research works in this dissertation focus onan overcomplete multi-scale transformation method-the nonsubsampled contourlettransform (NSCT) which has property such as multi-scale, multi-direction, anisotropyand translational invariance.Then we primarily research with the infrared and visiblelight image fusion algorithm and the multi-focus image fusion algorithm, moreover all the proposed algorithms are verified by Matlab7.5and VC++6.0tools.The main contributions of this dissertation can be summarized in the followingfive points:1. In-depth and comprehensive research with the nonsubsampled contourlettransform theory which has property such as multi-scale, multi-direction, anisotropyand translational invariance. After that we present the effects of the simulationexperiment in image decomposition and reconstruction with NSCT. At last weconstructed the framework and specific steps of the image fusion algorithms usedNSCT.2. Aiming at the infrared and visible light image fusion in the field ofmulti-source image fusion, we propose one kind of effective infrared and visible lightimage fusion algorithm which combined the improved OTSU regional segmentationand NSCT. On the basis of the characteristic of infrared and visible light imagesensors, regional segmentation and regional association are used in the source imagesat first, and then project the corresponding fusion rules to the NSCT decompositioncoefficients in different regions. This fusion algorithm achieved a most optimizedfusion method of the coefficients and effectively improved the quality of the infraredand visible light fused image.3. By theoretical analyzed the non-negative matrix factorization (NMF) theory,we detailed study on the projected gradient non-negative matrix factorization(PGNMF) and introduced it to the image fusion field. Experimental results indicatethat PGNMF either directly used in the source image fusion or used in the fusion rulesof NSCT decomposition low-frequency coefficient, it s able to reduce thecomputational complexity and time-consuming, when acquire manifest better fusedimage at the same time. Therefore, the proposed fusion algorithm can be used forreal-time image fusion system which called for less quality requirement of fusedimage. Moreover, we take both of the infrared and visible light image and themulti-focus image to experiment with the proposed fusion algorithm, to some extent,reflect the robustness of the algorithms. 4. By theoretical analyzed the particle swarm optimization (PSO) theory, wefound that PSO method is likely to converge prematurely and the lack of particlediversity lead the swarm to converge to the local optimum. Aimed at the disadvantageof PSO, combined with the artificial immune clonal selection theory, we proposed animproved clonal selection particle swarm optimization (ICSPSO), and the improvedalgorithm had application in multi-focus image fusion field successfully. The fusionalgorithm not only transforms the image fusion question as the optimization problemsbut also enhanced the fused image reliability and the fusion effect to a great extent.The better fusion effect and the lower time consumption causes ICSPSO fusionalgorithm to become one kind of effective fast image fusion algorithm.5. Introduced the compressed sensing (CS) theory to the image fusion field andproposed a new high-resolution image fusion algorithm based on CS. We alsocombined the CS and NSCT to resolve the high-resolution image fusion problem.Experimental results indicate that under the premise of slightly reducing the quality offused image, the proposed algorithm can greatly reduce the time-consuming. Therefor,the high-resolution image fusion algorithm based on compressed sensing is feasibleand effective, also can greatly reduce the time-consuming of the algorithm.
Keywords/Search Tags:image fusion, nonsubsampled contourlet transform, nonnegativematrix factorization, partical swarm optimization, compressed sensing, infrared andvisible light images, multi-focus images, fusion rules
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