Description: 基于粒子群优化算法(PSO)确定参数的脉冲欧和神经网络滤波方法。利用粒子群优化算法(PSO)确定pcnn图像滤波参数，对图像进行滤波-Based on Particle Swarm Optimization (PSO) to determine the parameters of the pulse in Europe and neural network filtering method. The use of particle swarm optimization (PSO) to determine PCNN parameters of image filtering, image filtering Platform: |
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Author:叶开 |
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Description: 这有三篇关于图像处理的论文，使用VC实现基于直方图的相对辐射校正，小波变换在图像处理中的应用，微粒群算法在图像处理中的应用研究，很有参考价值-There are three papers on image processing, the use of VC histogram-based relative radiometric correction, wavelet transform in image processing applications, particle swarm optimization in image processing applied research, the valuable Platform: |
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Author:英子 |
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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: |
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Author:吴琳珠 |
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Description: 本文提出了一种基于图像配准的自动目标识别算法,图像配准算法采用基于归一化互信息相似性判据,并采用模糊自适应粒子群优化算法作为搜索策略。在图像精确配准的基础上,通过图像间的相互转换,间接实现了目标的准确识别。仿真试验结果表明,该方法可以实现复杂背景下目标的准确识别。
-This paper presents a novel image registration algorithm for automatic target recognition, image registration algorithm based on normalized mutual information similarity criterion, and the fuzzy adaptive particle swarm optimization algorithm as search strategy. In the image on the basis of accurate registration, through the conversion between images, the accuracy of indirect recognition to achieve the target. Simulation results show that the complex background can accurately identify targets. Platform: |
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Author:wenping |
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Description: In this paper, a multimodal image fusion algorithm based on multiresolution
transform and particle swarm optimization (PSO) is proposed.
Firstly, the source images are decomposed into low-frequency coefficients and
high-frequency coefficients by the dual-tree complex wavelet transform
(DTCWT). Then, the high-frequency coefficients are fused by the maximum selection
fusion rule. The low-frequency coefficients are fused by weighted average
method based on regions, and the weights are estimated by the PSO to gain
optimal fused images. Finally, the fused image is reconstructed by the inverse
DTCWT. The experiments demonstrate that the proposed image fusion method
can illustrate better performance than the methods based on the DTCWT, the
support value transform (SVT), and the nonsubsampled contourlet transform
(NSCT). Platform: |
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Author:ishwarya |
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Description: 最大类间方差法是图像分割中一种常用的阈值分割方法, 对于单阈值分割具有显著的效果, 但是对于
多阈值分割, 计算复杂度大、耗时较多。本文将粒子群优化算法与最大类间方差法结合, 提出了一种新的图像分
割方法, 该方法利用粒子群优化算法的寻优高效性, 并由灰度图像的最大类间方差值作为适应值, 搜索最优分割
阈值, 实现图像的多阈值分割。实验结果显示, 新方法大大缩短了寻找最优阈值的时间, 降低了运算复杂度, 提
高了图像分割速度, 说明基于粒子群优化算法的图像分割算法是可行的、有效的。-Maximum between-class variance method is a popular image segmentation threshold segmentation method has a significant effect for the single-threshold segmentation, but
The multi-threshold segmentation, the computational complexity of large, time-consuming. In this paper, particle swarm optimization combined with maximum between-class variance method, a new image
Cut method, the method using particle swarm optimization algorithm optimizing the efficiency of the maximum between-class variance by the gray-scale image as the fitness value, search for the optimal split
Threshold, multi-threshold image segmentation. The experimental results show that the new method greatly shorten the time to find the optimal threshold, reducing the computational complexity, to mention
The high speed of image segmentation, image segmentation algorithm based on particle swarm optimization algorithm is feasible and effective. Platform: |
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Author:张泰然 |
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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: |
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Author:张泰然 |
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Description: 基于SVD的DCT域和DWT域的经典水印算法，该算法通过提取水印水印的主成分并把该主成分嵌入到奇异值矩阵，鲁邦性非常高。-the principal components of the watermark are embedded into the host image in discrete cosine transform (DCT) and for the second method, those are embedded into the host image in discrete wavelets transform (DWT). To improve the robustness, the particle swarm optimization (PSO) is used for finding the suitable scaling factors.
Platform: |
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Author:p2pgrid |
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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: |
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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: |
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Author:招伟杰 |
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Description: A color image quantization algorithm based on Particle Swarm Optimization (PSO) is developed in this
Platform: |
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Author:adnan ali |
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Description: 硕士论文，基于机器视觉苹果检测算法的研究。主要内容包括：1、国内外研究现状及进展 2、苹果图像采集与处理 3、苹果大小与形状检测 4、粒子群优化的BP神经网络苹果颜色检测算法 5、遗传算法优化BP神经网络苹果缺陷检测算法 6、苹果检测系统的软件、硬件及界面设计-Research on Apple detection algorithm based on machine vision. The main contents include: 1, the domestic and foreign research present situation and the progress of 2, apple image acquisition and processing 3, the shape and size of Apple detection 4, particle swarm optimization of BP neural network in apple color detection algorithm 5, genetic algorithm optimization BP neural network for Apple defect detection algorithm 6, apple detection system software, hardware and interface design Platform: |
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Author:吕吉方 |
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Search - particle swarm optimization in image