Image-point

运用小波阈值实现图像去噪，同时有小波的分解与重构。(Wavelet threshold is used to realize image denoising and wavelet decomposition and reconstruction.)

提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向 异性扩散（P-M扩散）两者的优点。通过P-范数方法选择合适的梯度阈值K，P-M扩散过程通过处理经过Curvelet 变换得到的图像的不同尺度的Curvelet 系数矩阵，实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。 实验表明，新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应，同时更好地保留图像的纹理和细节。 关键词：图像去噪算法；各向异性扩散；Curvelet 变换；P-M 扩散(Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed, which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.)

用matlab实现了分形，效果还是不错的，是分形学习中的基础内容(Matlab realize the use of fractal, the effect is still good, is a fractal study based on content)

这是图像处理中HSV课件颜色特征提取（将H5等份，S,V分量各三等份）MATLAB源码。(This is the image processing in HSV color feature extraction software (to be H5 equal, S, V component of the third class) MATLAB source.)

is very good,i think you will be liake it

多种图像处理基本方法的源代码，包括图像分割和边缘检测，非常适合初学者参考使用。(A variety of basic methods of image processing source code, including image segmentation and edge detection, is suitable for beginners reference.)

说明：  matlab编写的纹理图像分割 gussian滤波后k-means聚类 并将不同区域用线条表示出来(Matlab prepared texture image segmentation, Gussian filtering, K-means clustering and different regions are represented by lines)

基于梯度相似度的图像质量评价方法，发表在2012年TIP国际期刊上(A. Liu, W. Lin, M. Narwaria, “Image Quality Assessment Based on Gradient Similarity,” IEEE Transactions on Image Processing, vol. 21(4), pp. 1500-1512, 2012.)

利用极大似然估计进行盲反卷积复原，通过多帧图像约束，效果较好(Use of maximum likelihood estimates for blind deconvolution restoration by the multi-frame image constraint, the better)

几个流行的超图匹配代码 张量，随机游动，谱的(hyergraph matching)