BlurKernelEstimation

水平集分割图像的一种算法，属于比较前沿的一种图像分割方法。(A level set image segmentation algorithm, a relatively cutting edge of a segmentation method.)

基于分形理论的改进的一种图像分割算法,用matlab语言实现(Based on Fractal Theory An improved image segmentation algorithm)

说明：  使用硬/软阈值算法，求解各种不同范数约束问题，算法主要有三种(Contains three matrix completion algorithms and a demo script for running them. Also compares against other matrix completion algorithms - Singular Value Thresholding and Fixed Point Iteration.)

用于高光谱图像处理的最小噪声分离变换方法。(HYPERMNF Performs the minimum noise fraction (MNF) transform hyperMnf performs the minimum noise fraction (MNF) transform on the data and uses spatial (row) offsets of the data to estimate the covariance matrix of the data. Usage )

说明：  基于matlab的中值滤波算法，对图像进行去噪处理(median filtering algorithm based on matlab)

设计一个程序，对一幅灰度图像现直方图均衡化处理。画出均衡化前后的图像及其直方图 (histogram equalization )

利用PCA和模糊C均值相结合的方法实现图象的聚类(Using PCA and fuzzy C-means method of combining images to achieve the clustering)

MATLAB目标跟踪仿真小程序,对一定格式的AVI视频进行处理，提取出黑色背景下的人体轮廓及行动方向(MATLAB simulation of target tracking applet, for some form of AVI video processing, to extract the black outline and context of human action)

一个核fisher的代码，同样由matlab实现(A nuclear fisher code, also realize from matlab)

摘　要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不 适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的 舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。(Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2 ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2 pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3 b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack.)