src

很好的模糊聚类算法 用MATLAB编写的(Good fuzzy clustering algorithm using MATLAB prepared)

matlab3种内插法的实现。最近邻内插法，双线性内插法，双三次内插法的具体实现(To realize interpolation in matlab3)

能将一幅灰度图像根据用户自己给定的彩色图像将其对应的转化为真彩色图像。(Gray image can be processed into rgb image.)

用IDl编写的，用IDL图像处理。已调试好的程序。(Prepared using IDL with IDL image processing. Debugging process has been good.)

说明：  对图像进行哈夫曼编码并且能够解码，可以在命令行中选择图像地址(Huffman encoding and decoding of images)

对图片预处理加入高斯噪声，各种经典边缘检测算子对图像进行边缘提取(Gaussian noise on the image pre-processing, a variety of classic edge detection operator to extract image edge)

C# 放大和缩小图像 实例源码

圆阵常规波束形成与MVDR用于方位估计的比较，可以更改信噪比仿真两者的区别联系(uniform circle array based for estimating direct of arrival,CBF and MVDR compared with adjustable SNR)

采用多成分分析算法进行图像分解，并对该算法进行评价(MCA picture dissolution)

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).)