tsp_hopfield

LabWindows /CVI 大学实验指导书，难度循序渐进，一套下来，基本操作都会了。推荐一下(LabWindows/CVI University experiment instructions, the difficulty of step-by-step, set down, the basic operation will be. You recommend)

图像相似度计算，利用hog特征，不变矩，包含canny因子计算 来计算两张图片的相似度。可以用来进行图片检索(Image similarity calculation, hog characteristics, invariant moments contain a canny factor to calculate the similarity of two images. Can be used for image retrieval)

多个函数的曲线拟合，里面统计有最小二乘、非线性回归(Curve fitting for multiple functions)

数学形态学方法及其应用，老书不好找电子版啦，给大家发一个。超星版的(Mathematical morphology and its applications, the old books not easy to find electronic version of啦, give you hair a. Superstar Edition)

关于图像融合的工具箱，从国外网站上找到的，很好用，可以作为对比实验时使用。包含一些需要处理的源图像。(On image fusion toolbox, from abroad to find the site, very good, and can be used as a comparative experiment. Contains a number of source images need to be addressed.)

说明：  仿真获取四幅互差半个像素的低分辨率图像，利用反演解析算法重建出一副高分辨率图像，属于亚像元技术或者超分辨率技术。(Simulation Interoperability poor access to four half-pixel low-resolution images, the use of inversion algorithm for the reconstruction of an analytic high-resolution images, belong to sub-pixel super-resolution technology or technology.)

高斯平滑滤波实例，高斯滤波实质上是一种信号的滤波器，其用途是信号的平滑处理，我们知道数字图像用于后期应用，其噪声是最大的问题，，由于误差会累计传递等原因，很多图像处理教材会在很早的时候介绍Gauss滤波器，用于得到信噪比SNR较高的图像（反应真实信号）。 (Instance of the Gaussian smoothing filter, Gaussian filter is essentially a signal filter, its purpose is to smooth processing of the signal, we know that the digital image for the late application, the noise is the biggest problem, the error accumulated transfer reason, a lot of image processing textbooks will be introduced at an early Gauss filter for higher SNR of the image (real response signal).)

说明：  前馈神经网络图像去噪，DnCNN的MATLB实现，以及相应的峰值信噪比和结构相似性的计算。(DnCNN,MATLAB,And calculation of peak signal-to-noise ratio structural similarity)

说明：  利用边界匹配算法恢复受损图像寻找最优运动矢量(edge detection function [hough_space,hough_circle,para] = hough_circle(BW,step_r,step_angle,r_min,r_max,p) )

基于颜色衰减先验模型的单幅图像快速去雾算法。(A Fast Single Image Haze Removal Algorithm using Color Attenuation Prior)