ICM

说明：  计算两个离散变量x和y的联合熵z = H（x，y）。 输入：x，y：两个相同长度的整数向量输出：z：联合熵 可以使用，有利于学习目的(Compute joint entropy z=H(x,y) of two discrete variables x and y. Input: of x, y: two integer vector of the same length Output: z: joint entropy good for learning purposes)

说明：  基于小波变换的图像融合，可实现两幅图像的融合，融合规则可自定义(Image fusion based on wavelet transform can realize the fusion of two images, and the fusion rules can be customized)

利用霍夫曼方法进行图像的霍夫曼编码与解码(Hoffman method using images of the Hoffman encoding and decoding)

说明：  基于OpenCV的MPEG-7特征提取，c++代码(MPEG-7 feature extraction based on OpenCV)

利用图像处理的方法实现图像二值化，实现了图像的调幅加网，加网角度是18.4度。这就方便了图像的调幅加网输出。(The use of image processing method of image binarization realize, realize the image of AM screening, screening angle is 18.4 degrees. This facilitates the image output of AM screening.)

基于纹理度量的图像分割，适用于遥感图像，利用到K-mean算法(texture measurement based on the image segmentation, applicable to remote sensing images, the use of K-mean algorithm)

最经典之做，保证别人没有上传过 实现文章 “GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts 用graphcut实现图像分割，效果非常好(The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results)

实现高斯模糊，运动模糊等的点扩展函数psf的估计，并复原(The estimation of point spread function PSF, such as Gauss blur and motion blur, is realized and restored.)

程序为读取图片并对图片进行边缘检测，先采用高斯滤波进行去噪，然后通过求梯度运算检测，非极大值抑制边缘检测，双阈值检测这三种方法，分别对图片进行边缘测，并对边缘检测后显示的图片进行对比。此程序对边缘检测有很大的参考价值。(Program to read the image and image edge detection, Gaussian filter to remove noises, and then detected by calculating the gradient operation, the non-maxima suppression edge detection, dual-threshold detection of these three methods, namely the picture edge test, and the rear edge detection to display image comparison. This program is great for edge detection reference value.)

数字图像的几何校正，有效解决因为视角不正确、设备等因素引起的图像几何上的变形(Geometric correction of digital images, an effective solution to the deformation on the geometry of the image because the perspective is not correct, equipment, and other factors...)