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自动种子区域生长代码，用MATLAB运行，不必选择种子点 可以自动选择阈值 实现图像分割！(The automatic seed region growing code, run, do not have to select seed point can automatically select the threshold image segmentation using MATLAB)

基于空域的脆弱水印，可以有效检测出图像发生篡改的区域(Airspace based on fragile watermarking can effectively detect the occurrence of tampering with the image of the region)

MR核磁共振图像重建算法 MR image reconstruction(MR magnetic resonance image reconstruction algorithm for MR image reconstruction)

Jpeg2000静态库，只需Encoder和Decoder两个函数轻松搞定Jpeg2000和Bitmap的转换，带示范程序，非常有用(Jpeg2000 static libraries, Encoder and Decoder only two functions easy to get and Bitmap Jpeg2000 The change model procedures with very useful)

用Python语言实现Poisson Image Editing（泊松图像编辑）算法(implementation of Poisson Image Editing algorithm with python.)

Retinex理论的基础理论是物体的颜色是由物体对长波（红色）、中波（绿色）、短波（蓝色）光线的反射能力来决定的，而不是由反射光强度的绝对值来决定的，物体的色彩不受光照非均匀性的影响，具有一致性，即retinex是以色感一致性（颜色恒常性）为基础的。不同于传统的线性、非线性的只能增强图像某一类特征的方法，Retinex可以在动态范围压缩、边缘增强和颜色恒常三个方面打到平衡，因此可以对各种不同类型的图像进行自适应的增强。(The basic theory of Retinex theory is the color of the object by object for the long wavelength (red), medium (green), short wave (blue) light reflection ability to decide, rather than by the intensity of reflected light of the absolute value to decide, the color of the object under illumination nonuniformity effects, consistent with the Retinex, that is based on color constancy (color constancy based). Different from the traditional linear, nonlinear image enhancement method of only one kind of features, Retinex can be in dynamic range compression, edge enhancement and three aspects of color constancy hit the balance, thus enhancing adaptive to a variety of different types of images can be.)

能计算图像的灰度直方图，及其对应的灰度均值(calculate means ，variance，bins)

说明：  旋转，利用双线性插值实现重采样，基于c++与opencv(Rotation, resampling by bilinear interpolation, based on C + + and opencv)

OPENCV图像处理模板，有界面编程的，以后运用opencv直接在里面填写代码就可以了(OPENCV image processing template, with interface programming, and after using opencv code directly on the inside can be a complete)

基于凸集投影算法的超分辨率图像重建算法，在现有算法基础上改进计算精度和效率。(To improve the computational accuracy and efficiency in the existing algorithms based on super-resolution image reconstruction algorithm based on projections onto convex sets algorithm.)