Unit7SDG

图像的相关系数是衡量两幅图像的相关程度的，本代码直接通过选定区域计算出相关系数！(image correlation coefficient is a measure of two images of the code directly through selected regional correlation coefficient calculated!)

说明：  获取线上美女图片，其实也就是一个抓取程序(catch lady‘s photo)

说明：  这个文件中包含了三种图像相似度的计算方法，分别是灰度分布计算方法、颜色分布直方图计算方法、还有结构相似度SSIM计算方法。(This file contains three image similarity calculation methods, namely, gray distribution calculation method, color distribution histogram calculation method, and structure similarity SSIM calculation method.)

简单起见，这里设定阈值为122，即最大灰度的一半(the sake of simplicity, this threshold value is set to 122, the largest gray half)

sift详细编写,方向等参量，参数取舍详细(sift Detailed compilation of sift, direction and other parameters, detailed selection of parameters sift sift sift sift)

何恺明等人研究出的基于暗通道的经典图像去雾算法，不仅可以还原图像的颜色和能见度，同时也能利用雾的浓度来估计物体的距离。(The classic fog removal algorithm based on dark channel, which was developed by He Kaiming and others, not only can restore the color and visibility of images, but also can estimate the distance of objects by using the concentration of fog.)

基于多阈值的图像分割()

数字图象处理算法的演示，包括：图象的DFT和逆DFT，图象的FFT和逆FFT，在图象中加入正弦噪声，图象的模板运算实现图象平滑和锐化等等。(digital image processing algorithms demo, including : Image DFT and inverse DFT, FFT image and inverse FFT, in the image by adding sinusoidal noise, the template image Operational Image sharpening and smoothing and so on.)

C++调试的背景的颜色改为比较对眼睛好看的颜色呢(C++ debugging change the color of the background of relatively good-looking colors for the eyes)

超像素分割方法，在计算机视觉领域，图像分割（Segmentation）指的是将数字图像细分为多个图像子区域（像素的集合）（也被称作超像素）的过程。超像素有一系列位置相邻且颜色、亮度、纹理等特征相似的像素点组成的小区域。这些小区域大多保留了进一步进行图像分割的有效信息，且一般不会破坏图像中物体的边界信息。(Super pixel Segmentation method, in the field of computer vision, image Segmentation, Segmentation) refers to the digital image Segmentation region for multiple image sequence (the set of pixels) (also known as the pixels) process. Adjacent pixels have a series of position and features such as color, brightness, texture similar to that of small region composed of pixels. Most of these small area retains the further effective information for image segmentation, and generally does not destroy the boundary of the object in the image information.)