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1.
In this paper,a new image reconstruction algorithm named maximum entropy reprojecting is developed for missing projection data from some objects are opaque for parts of ray.The results of comparing simulation experiments on the general computer indicate that the quality of reconstructed images by the new algorithm are much better than the tradional maximum entropy algorithm.So the algorithm has reliable propect in application.  相似文献   

2.
The Recursive Orthogonal Least Squares (ROLS) algorithm is applied to train Radial Basis Function Neural Network (RBFNN) when modeling, so as to save large memory and computational efforts. Using the information available from the trained network with ROLS algorithm, the effective centers of network can be obtained by adopting backward selection algorithm, which achieve acceptable accuracy with significant reduction of network structure. The results of simulation and experimentation show that the algorithm is efficient and useful.  相似文献   

3.
遥感影像土地利用/覆盖分类方法研究进展   总被引:4,自引:0,他引:4  
为了研究遥感影像土地利用/覆盖分类的方法,综述了国内外近30年的遥感图像分类研究,发现遥感图像分类方法存在多而杂的问题。在分析当前主要遥感影像分类方法的基础上,从传统的分类方法、传统分类方法的改进、其他新分类方法3个方面,对遥感影像土地利用/覆盖分类方法研究进展进行了阐述,本研究还存在不足,今后还需进一步研究利用各种分类方法相互结合在土地利用/覆盖遥感分类中的应用。  相似文献   

4.
By the definition and interpretation of directional elemental pixel sets, a method for getting the directional image from the binary fingerprint image using the statistic characteristics of DEPS is presented in this paper. This method is better than traditional methods in processing speed, computing complexity and resisting noises. The directional image got by this method is used to the matching of ridges frame in a fingerprint verification system, and the testing result shows that the method is effective.  相似文献   

5.
[Objective] The aim of this study was to improve the cotton image segmentation accuracy in a picking robot image processing system. [Method] An image segmentation algorithm based on a fusion method of Markov random field and quantum particle swarm optimization clustering was proposed. The process of the proposed algorithm is as follows: first, transform the RGB (red, green, blue) images into grayscale; second, use it to segment these images; finally, the threshold of the connected area is set on the basis of the segmented image to obtain the target area. Then, the cotton front image and the cotton side image are selected from the images collected from different angles. The segmentation experiment was carried out by using this algorithm, and compared with the Otsu algorithm, the fuzzy C-means algorithm, the quantum particle swarm image segmentation algorithm and the Markov random field image segmentation algorithm. [Result] The results showed that the segmentation accuracy and peak signal to noise ratio of the proposed algorithm were 98.94% and 77.48 dB. When compared with the Otsu algorithm, fuzzy C-means algorithm, quantum particle swarm optimization algorithm and Markov random field algorithm, the average segmentation accuracy and peak signal to noise ratio of the proposed algorithm increased by 2.47%–4.56%, and 9.81–13.11 dB, respectively. [Conclusion] The proposed algorithm had higher segmentation accuracy and higher peak signal to noise ratio than the other algorithms tested.  相似文献   

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