diskreet.m

说明：  利用遗传算法进行图像分割(matlab源码)(The use of genetic image segmentation algorithm (matlab source))

显示处理后的BMP图像文件，VC C++ (read the bmp images )

说明：  该算法利用概率论中最大似然估计实现EM算法，通过对理论图像和统计图像的比较得出结果。(The algorithm uses the probability of the maximum likelihood estimate EM algorithm, the results of the comparison of theoretical imagery and statistical image.)

遗传算法与FCM算法相结合实现图像分割，分割精度较好，速度较快(A combination of genetic algorithm and FCM algorithm to achieve image segmentation, segmentation accuracy is better, faster)

说明：  显著性检测的代码，是程明明在12年的CVPR的文章，HC,RC的算法源码。(The code for saliency detection is the source code of Cheng Mingming's CVPR article, HC, RC, in 12 years.)

图着色问题（Graph Coloring Problem, GCP）又称着色问题，是最著名的NP-完全问题之一。路线着色问题是图论中最著名的猜想之一。(Graph coloring problem (Graph Coloring Problem, GCP), also known as coloring problem, is the most famous NP-complete problems. Line graph coloring problem is one of the most famous conjecture.)

运动模糊图像的复原，涉及运动图像的模糊方向和模糊尺度的确定，然后运用维纳滤波(motion blur image recover)

冈萨雷斯数字图像处理第二版中的tofloat函数，原书配带的函数式p文件，此处已经转为M文件。(Gonzalez Digital Image Processing Second Edition tofloat function, a function of the original book equipped with p-type documents, here has been converted to M-file.)

图像融合中的平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等(Average gradient, correlation coefficient, information entropy, cross-entropy, joint entropy, mean square error, mutual information, signal-to-noise ratio, peak signal-to-noise ratio, root mean square error, spatial frequency, standard deviation, mean, distortion degree, deviation index, etc. in image fusion)

本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望(In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and then systematically introduces the basic concept of the technology and data models for today' s more popular variety of independent component analysis algorithm is analyzed and summarized. Finally, independent component analysis of the development and application prospects are described)