MATLAB_Image_subpixel_Mutual_info

实现shift算法，进行精确的图像识别，可以抵抗各种旋转、平移、缩放等仿射变换的攻击(Realize shift algorithm, an accurate image recognition, you can resist all kinds of rotation, translation, scaling affine transformation attack)

基于像素点的全局阈值法求图像的分割 实现方法有五种： 最小极值法，最优阈值法，最大方差方法，最大熵法，迭代法(Pixel-based global threshold method for image segmentation method there are five: the smallest extreme value method, the optimal threshold method, the largest variance method, the maximum entropy method, iterative method)

说明：  自己写的Active Shape Model face segmentation 代码 (Write their own Active Shape Model face segmentation code)

采用Graph Cut算法进行multiple-label的图像分割，算法很完整，非常适合初学者以及开发人员参考(multiple-label image segmentation using Graph Cut based algorithm, suitable for beginners and developers)

压缩感知重建算法,利用压缩感知理论实现用较少的采样量恢复出高分辨率的图像信息(compressive sensing reconstruction algoriyhm)

说明：  matlab最小二乘法曲面拟合程序可以得到函数具体解析式(Matlab least squares surface fitting program can get the specific analytic expression of the function)

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)

说明：  ：建立了碳钢渗硫表面和非渗硫表面的多球凸峰面接触模型，模型中，凸峰高度按高斯函数分布．用塑性流线 理论分析了渗硫层的摩擦系数．计算结果表明：摩擦系数随载荷的增加而增加；相同粗糙度下，磨削加工的摩擦系 数比车削加工的摩擦系数大；摩擦系数随着渗层厚度的增大而增大．从减小摩擦系数的角度来考虑，渗硫层并非 越厚越好． (the multi-asperity sphere-shape model for surface contact between sulphurized layer and unsulphurized layer is established．in which the height of sphere-shape asperities follows the Gaussian distribution．1he frictional coeficients of sulphurized layers are analyzed by using plastic flown line theory．1he results show that the frictional coeficient increases with the load．the frictional coeficient of ground surface is higher than that of tumed surface in case of the same roughness．1he thicker the sulphuri[ed layer is．the higher the frictional coeficient is．From the viewpoint of reducing frictional coeficient，the thickness of sulphurized layer should be smaller．)

图像分割是图像分析的关键步骤，而水平集方法是图像分割的一项热门方法，它有着许多算法不具有的优点，尤其可用于分割背景复杂信息难以提取的医学图像。这里是一些水平集分割图像的matlab的实现例子，希望可以帮到大家。(Image segmentation is the key step of image analysis, while the level set method is a popular image segmentation method, it has many advantages that the algorithm does not have, especially can be used for medical image segmentation of complex background information is difficult to extract. Here is some level set segmentation image matlab example, I hope we can help you.)

首先通过多分辨率分解法提取高频边缘，然后分别对每层的高频边缘进行非线性插值得到新的高频边缘，接着对高频边缘进行高通滤波得到等强后的高频边缘，最后对增强后的高频边缘进行修正。再在对增强的图像进行对比度拉伸，从而达到增强的目的！(First of all, through the extraction of multi-resolution decomposition of high-frequency edge, and then were on the edge of each high-frequency non-linear interpolation to be the new high-frequency edge, and then the edge of the high-frequency high-pass filter to be strong, such as after the high-frequency edge, and finally on the brink of enhanced high-frequency be amended. Again in contrast enhanced image stretching, so as to achieve the purpose of enhancing!)