Description: 采用粒子群矢量量化算法生成图像矢量量化的最优码书，可以任意设定种群数与迭代代数。程序结果产生最优码书与平均误差。-Vector quantization using particle swarm algorithm for optimal image vector quantization code book, can set the number of stocks and iterative algebra. The results of the proceedings arising from the optimal codebook with an average error. Platform: |
Size: 51200 |
Author:张冰 |
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Description: 多阈值图像分类的粒子群优化算法，采用自然方法来提高优化速度和计算量-Multi-threshold image classification of the particle swarm optimization algorithm, using natural methods to improve the optimization speed and computation Platform: |
Size: 2048 |
Author:baiyilieren |
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Description: 对不同噪声强度的加噪图像，用粒子群优化算法优化结构元素，找到最优结构元素，对图像进行去噪操作，使恢复的图像达到最大峰值信噪比-Noise intensity for different images with noise, using particle swarm optimization algorithm to optimize the structure elements, find the optimal structure element, the image de-noising operation to restore the image to a peak signal to noise ratio Platform: |
Size: 130048 |
Author:吴琳珠 |
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Description: 利用克隆选择和粒子群算法实现图像分割 有很好的分割效果。经过多次验证实践。-Clonal selection and particle swarm algorithm has a good image segmentation segmentation. After several rounds of verification practice. Platform: |
Size: 4096 |
Author:tanjing |
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Description: 为了提高算法的执行效率, 应用粒子群算法求取图像中任意两点间最短路径来定位目标边界, 并与经典的基于Dijkstra 动态规划图搜索的Liv e Wire 算法进行比较.-In order to improve the efficiency of the algorithm, particle swarm algorithm to strike any of images to locate the shortest path between two object boundaries, and with the classical dynamic programming graph search based on Dijkstra' s algorithm to compare Liv e Wire. Platform: |
Size: 318464 |
Author:莉 |
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Description: 本文件是一个细菌觅食粒子群算法，在数字图像处理中的应用。-This document is a bacterial food particle swarm algorithm in the digital image processing applications. Platform: |
Size: 2452480 |
Author:杨 |
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Description: 提出一种基于粒子群优化算法的图像矢量量化码书设计算法. 该算法引入粒子群的全局搜索策略 , 结合矢量量化码书设计方法 , 增加了算法解的随机性和多样性.-Proposed based on particle swarm optimization algorithm for image vector quantization codebook design algorithm. The introduction of particle swarm algorithm global search strategy, combined with vector quantization codebook design methods, solutions to increase randomness of the algorithm and diversity. Platform: |
Size: 289792 |
Author:小潘 |
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Description: 针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷
入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。
该方法考虑了图像中像素点灰度 邻域灰度均值对作为阈值对图像进行分割 利用混沌运
动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜
索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索
时间, 提高了收敛率。-Calculation of its large capacity and particle swarm algorithm is easy to fall to strike the best threshold for the two-dimensional entropy image segmentation method
Into the local optimum and slower, the proposed two-dimensional entropy image segmentation method based on chaotic particle swarm optimization algorithm.
The method takes into account the image pixel the gray neighborhood average gray value as a threshold for image segmentation chaotic transport
Dynamic randomness, ergodicity and initial value sensitivity of chaotic particle swarm optimization algorithm with the threshold method in two-dimensional space for the global search
On request. Experimental results show that the entropy method of image segmentation method based on chaotic particle swarm optimization algorithm for threshold optimization to reduce the search
Time and improve the convergence rate. Platform: |
Size: 1820672 |
Author:张泰然 |
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Description: 将粒子群算法应用到图像边缘提取中，有一些参数可能要根据具体的情况做一些修改-The particle swarm algorithm applied to the image edge extraction, some parameters may have to make some changes according to the specific situation Platform: |
Size: 134144 |
Author:ptlove |
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Description: 摘 要 为了实现快速精确的图像配准， 提出了基于改进粒子群优化算法的互信息图像配准方法， 以互信息作为图像配准的相似性测度， 使用改进的 PSO 算法来求解配准所需的空间变换参数 改进的粒子群算法引入组织的概念把整个种群划分为多个子群体共同进化， 并引入变异运算减少算法陷入局部最优 把改进的粒子群优化算法应用到医学图像配准领域上来， 实验结果表明， 算法能够得到比较满意的配准结果-Abstract In order to realize the fast precise image registration，a mutual information image registration method based on improved particle swarm optimization is proposed. Mutual information is used as the similar measure. The improved particle swarm optimization algorithm solves the space transformation parameters of registration. The organization concept is introduced in the method to divide the entire population into several sub－groups，meanwhilthe mutation operation in genetic algorithm is introduced to reduce the local extreme. And improved PSO is used in the medical image registration. The results show that the method can achieve more satisfied results of the image registration. Platform: |
Size: 191488 |
Author:vivi |
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Description: 实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。
对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。
深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。
利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。
-SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification. Platform: |
Size: 1626112 |
Author:招伟杰 |
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