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Fuzzy image restoration using modulation transfer function
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作者 袁媛 Yi Yaohua Liu Juhua 《High Technology Letters》 EI CAS 2016年第4期461-469,共9页
The key difficulty of restoring a fuzzy image is to estimate its point spread function( PSF). In the paper,PSF is modelled based on modulation transfer function( MTF). The first step is calculating the image MTF. In t... The key difficulty of restoring a fuzzy image is to estimate its point spread function( PSF). In the paper,PSF is modelled based on modulation transfer function( MTF). The first step is calculating the image MTF. In the traditional slanted-edge method,a sub-block is always manually extracted from original image and its MTF will be viewed as the result of the whole image. However,handcraft extraction is inefficient and will lead to inaccurate results. Given this,an automatic MTF computation algorithm is proposed,which extracts and screens out all the effective sub-blocks and calculates their average MTF as the final result. Then,a two-dimensional MTF restoration model is constructed by multiplying the horizontal and vertical MTF,and it is combined with conventional image restoration methods to restore fuzzy image. Experimental results indicate the proposed method implementes a fast and accurate MTF computation and the MTF model improves the performance of conventional restoration methods significantly. 展开更多
关键词 fuzzy image modulation transfer function(MTF) slanted-edge method automatic computation MTF restoration model
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SOFT IMAGE SEGMENTATION BASED ON CENTER-FREE FUZZY CLUSTERING 被引量:2
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作者 马儒宁 朱燕 丁军娣 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2013年第1期67-76,共10页
Image segmentation remains one of the major challenges in image analysis.And soft image segmentation has been widely used due to its good effect.Fuzzy clustering algorithms are very popular in soft segmentation.A new ... Image segmentation remains one of the major challenges in image analysis.And soft image segmentation has been widely used due to its good effect.Fuzzy clustering algorithms are very popular in soft segmentation.A new soft image segmentation method based on center-free fuzzy clustering is proposed.The center-free fuzzy clustering is the modified version of the classical fuzzy C-means ( FCM ) clustering.Different from traditional fuzzy clustering , the center-free fuzzy clustering does not need to calculate the cluster center , so it can be applied to pairwise relational data.In the proposed method , the mean-shift method is chosen for initial segmentation firstly , then the center-free clustering is used to merge regions and the final segmented images are obtained at last.Experimental results show that the proposed method is better than other image segmentation methods based on traditional clustering. 展开更多
关键词 soft image segmentationl fuzzy clusteringl center-free clusteringI region merging
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Practical Issues Concerning Moment Invariants
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作者 Xiaojian Xu & A.G. Constantinides (Beijing Institute of Environment Features)(Depatment of Electrical and Electronic Engineering Imperial College of Science,Technology and Medicine) 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1996年第1期43-57,共15页
In this report several practical issues about moment invariants with application to image classification are concerned. A modified formulation for the approximation of the moments of digital images is suggested. Four ... In this report several practical issues about moment invariants with application to image classification are concerned. A modified formulation for the approximation of the moments of digital images is suggested. Four computational procedures and their corresponding noise performances are studied in detail. 展开更多
关键词 Pattern recognition image processing Momeent invariant fuzzy logic.
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