varErrorDiff

用C语言解决TSP问题的源程序是我大二选修数学建模课,课程结束后做大作业也就是选择一个题目,解决一个问题,我选择的是TSP()

对图像进行平滑去噪，提高图像的质量，为后期的图像处理打基础(very good)

说明：  基于分水岭变换的浮选泡沫图像分割基于分水岭变换的浮选泡沫图像分割(GOODGOODGOODGOODGOODGOODGOODGOOD)

对两幅图像进行配准，分别提取两幅图像的surf特征点以及描述子，得到粗匹配结果，然后根据粗匹配结果，采用ransac方法计算基础矩阵，并去除误匹配点，得到较准确匹配结果(Two image registration, surf was extracted from the feature points in two images to get the coarse matching and descriptor, then according to the results, the coarse matching results, using RANSAC method to calculate the fundamental matrix, and eliminate the error matching, gain a more accurate matching results)

meanshift图像分割 1.mean shift 的迭代过程只做了一次（为了简单） 2.对图像中的某一点进行平移时，只考虑了距离它小于2*hr的点，而不是图像中所有的 点。 3.实验过程中只用到了gauss核，虽然提供了method的选择，但在进行值域加权时只用 到gauss核，如果需要请自己改正。(meanshift segmentation)

利用图像差分，进行人体跟踪，并记录视频帧中目标的坐标，（PS:没有上传视频模板）(Differential use of image for the human body tracking, and record the video frame in the coordinates of the target, (PS: do not upload videos template))

利用MATLAB进行血管的三维图像重建,充分利用了matlab对大量图片的处理能力(The use of MATLAB to carry out three-dimensional image reconstruction of blood vessels, matlab full advantage of the large number of image processing capability)

提取特征点并匹配，有基于相关系数和最小二乘两种方法。(Extracting feature points and matching)

数字图像质量评价量：计算数字图像在基于像素统计差异、基于相似性度量统计差异、基于频谱统计差异以及基于人眼视觉系统统计差异等的图像质量评价量(Digital image quality evaluation of the volume: calculating the number of images in the pixel-based statistical difference, similarity measure based on statistical differences, based on statistical difference spectrum, as well as human visual system based on statistical differences in image quality evaluation of the volume of)

中值滤波程序 对图象选定区域进行排列中值 滤波(median filtering of images selected procedures region with median filtering)