Harris

通过稀疏重构一幅自然图像，使得该图像重新生成，同时找出稀疏系数。(One kind of denoising signal sparse representation)

非局部平均，用来去除灰度图里面的噪声，效果明显(Probability Non-Local Means)

使用PCA和SVD进行数据去噪，利用数据主要的特征向量进行数据恢复和重建(Using PCA and SVD for data denoising)

说明：  图像盲复原，图像非盲复原，利用低秩分解进行图像盲复原处理，RPCA模型算法，GoDec模型算法。(Blind image restoration, non-blind image restoration, low rank decomposition)

本程序是基于图论的知识进行图像分割，其中用到的是graphcut分割知识，完整的程序代码及结果！！(This procedure based on the knowledge of graph theory for image segmentation, which is used graphcut segmentation knowledge, including program code and the complete results !!)

首先生成如下形式的图片：图中的白条为7象素宽，210象素高，白条间的宽度为17象素。 应用多种滤波器进行处理：算术均值，几何均值，谐波均值，逆谐波均值，中值滤波，中点滤波，最大值、最小值滤波等。注意，需改变模板大小。详细比较上述的结果，并分析原因。 (First generation following form images: figure IOUs 7 pixels wide, 210 pixels high, the width is 17 pixels between IOUs. Using a variety of filters for processing: the arithmetic mean, geometric mean, harmonic mean, inverse harmonic mean, median filtering, filtering midpoint, maximum, minimum filtering. Note that the need to change the template size. A detailed comparison of these results and analyze the reasons.)

说明：  图像稀疏编码的一种方法，可用于基于稀疏表示的图像压缩、去噪等(Sparse image coding method can be used for sparse representation-based image compression, denoising, etc.)

说明：  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)

说明：  matlab使用regionprops求面积，找到连通域(Matlab uses regionprops to calculate area and find connected region)

说明：  一个线性积分卷积（LIC)matlab源码(A linear integral convolution (LIC) matlab source)