second-gray-image-statistics-and-FFT

c# 饼形图分析公司男女比例 附源码

转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)

MCA为形态学成分分析 将图像分为纹理和结构两个部分(MCA method of image decomposition texture and structure)

说明：  可评价影像融合质量，信息熵、标准差、相关系数等(Evaluable image fusion quality, information entropy, etc.)

局部熵差图象匹配并行算法的分析和 功能以及和其他算法的比较(err)

基于频率锁定环路和相位锁定环路级联，高斯噪声下的高动态实现载波跟踪(Based on frequency-locked loop and a phase locked loop cascade, the Gaussian noise high dynamic carrier tracking)

说明：  直方图均衡化,直方图均衡化vc++源代码(histogramequalization)

用于对灰度图像的双边滤波，程序简单易懂，还有很强的可开发性(Bilateral Filtering)

针对多聚焦图像融合，采用基于小波分解和点扩展函数模型PSF相结合的融合方法。(For multi-focus image fusion, based on wavelet decomposition and the point spread function PSF model combining fusion.)

自适应直方图均衡算法，对彩色图像的处理，有很好的效果。尤其是针对医学图像，内窥镜图像。(Adaptive histogram equalization algorithm for color image processing, have a good effect. Especially for medical images, endoscopic images.)