target

说明：  该代码能够实现K均值聚类算法对彩色图像分割，在MATLAB下实现。(The code can achieve K means clustering algorithm to color image segmentation, in MATLAB to achieve.)

利用小波包分解对一个二维含躁图像进行去噪处理(Using Wavelet Packet Decomposition to Denoise a Two-Dimensional Fidgety Image)

自己编写的二维傅里叶变换的源代码，并在变换后显示频谱。(Two-dimensional Fourier transform of the source code I have written, and displayed in the transformed spectrum.)

基于matlab的高帽变换，能很好地对图像进行一定的处理，实现图像的增强，线性特征的提取，为后续的处理做准备(Matlab-based top-hat transform good image processing, image enhancement, linear feature extraction, to prepare for subsequent processing)

灰度图像到RGB彩色的伪彩色图像的转变程序(Gray-scale image to RGB color of the pseudo-color image change procedures)

这是一种彩色图像去雾算法，可以识别物体的轮廓，但是同时也会加强这些轮廓，虽然去雾效果不错，但是会加强轮廓！(This is a color image to fog algorithm can identify the contours of the object, but will also enhance the outlines, although to fog effect is good, but will strengthen the profile!)

此程序计算的是两幅图像的峰值信噪比，运行流畅(This program calculates the peak signal to noise ratio of the two images, run smoothly)

运用HOG提取人脸特征与支持向量机算法训练模型，进行人脸识别(Using HOG to extract facial features and support vector machine algorithm training model for face recognition)

说明：  本文以k-means算法为背景，引入信息熵相关知识，从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时，会发生一定的过拟合现象，导致我们得不到预期的聚类数目。本文设计合理的合并准则，令模型简化，有效地消除过拟合现象，使得最后得到的聚类数目与预期符合。，设计合理的准则改进了图像的全自动分割方法，使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.)

熟悉图像的频域滤波算法、灰度图经FFT 后变到频域、噪声及移除(Familiar image of the frequency domain filtering algorithm, after the change to grayscale by the FFT frequency domain, noise and removed)