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【期刊论文】GAUSSIAN NOISE FILTER BASED ON PCNN
马义德, Ma Yi-de, Shi Fei, Li Lian
,-0001,():
-1年11月30日
Pulse Coupled Neural Network (PCNN) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammal's visual cortex. PCNN is a model with multiple parameters, and finding the proper values of these parameters is an onerous task. So a simplified PCNN is put forward and its performance in removing Gaussian noise of image is discussed in this article. The algorithm of PCNN combined with median filter and the step-by-step modifying algorithm, which is also based on PCNN, are proposed, and the experiment results of the two algorithms are analyzed and compared with that of median filter and wiener filter.
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马义德, Ma Yi-de, Yang Miao
,-0001,():
-1年11月30日
A method for optimal complex rank-order morphological filters with hybrid genetic algorithm is presented in this paper. It combined simulated annealing genetic algorithm (SAGA) with adaptive genetic algorithm (AGA) to achieve optimal filtering parameters in a global searching. Experimental results show that this method is practical, easy to extend, and improves the performances of the complex rank-order morphological filters. By means of adaptive optimizing training the percentile and the structuring elements, morphological filters possess the shape and structural system characteristics of image targets. Complex rank-order morphological filters formed in this way become intelligent and can provide good filtering results and robust adaptability to image targets with clutter background.
order statistics,, complex rank-order morphological filters,, genetic algorithms,, optimization algorithms,, image processing
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【期刊论文】An Improved Algorithm Based on Extremum and Median Value*
马义德, MA Yide, YANG Miao and ZHANAG Xiangguang
,-0001,():
-1年11月30日
The extremum and median filter can not only preserve the details of image as much as possible but aslo remove the noise when the grayscale changed gently. But, it's not very effective when processing those images including extremum areas. A new algorithm is presented in this paper and it solves the problem is presented in this paper and it solves the problem existing in formet filter. The experimental results show that the method is quite effective on most images and has better performance.
Nonlinear filter,, Median fllter,, Extremum median filter,, Similaity function.,
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马义德, MA Yide, , DAI Rolan and LI Lian
Chinese Journal of Electronics Vol. 11, No.1, Jan. 2002,-0001,():
-1年11月30日
A new, simple method of counting and segmenting cell image is suggested in this paper. It is based on the feature of cell's logical and morphological iafornmation. By using of mathematics, n, morphological, logical operation and laplacian fiter, the method is realized with the MATLAH 5.10. The segment effect of this algorithm is tested with blood cell image in this article and the result is desirable, Particularly this method can count the number of blood cells. However, this counting is not very accurate, but it is enough for biological research of cytologlcal count. At the same time this method can segment special blood cell from its neighhorhood, which is very important for the development of image scgment technology, because traditional image segment method is inadequate to achieve such segment and count of calls.
Logical operation,, Cell image,, Mor phalogical operation,, Laplaclan filter.,
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【期刊论文】Image segmentation of em-bryonic plant cell using pulse-coupled neural networks
马义德, MA Yide, , DAI RolanT, LI Lian & WEI Lin
Chinese Science Bulletin Vol. 47 No.2 January 2002,-0001,():
-1年11月30日
Traditional image segmentation algorithms exhibit weak performance for plant cells which have complex structure. On the other hand, pulse-coupled neural network (PCNN) based on Eckhorn's model of the cat visual cortex should be suitable to the segmentation of plant cell image. But the present theories cannot explain the relationship be. tween the parameters of PCNN mathematical model and the effect of segmentation. Satisfactory results usually require time.consuming selection of experimental parameters. Mean-while, in a proper, selected parametric model, the number of iteration determines the segmented effect evaluated by visual judgment, which decreases the efficiency of image segmentation. To avoid these flaws, this note proposes a new PCNN algorithm for automatically segmenting plant embryonic cell image based on the maximum entropy principle. The algo-rithm produces a desirable result. In addition, a model with proper parameters can automatically determine the number of iteration, avoid visual judgment, enhance the speed of' segmentation and will be utilized subsequently by accurate quantitative analysis of micro.molecules of plant cell. So this algorithm is ainable for theoretical investigation and application of PCNN.
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