MRF-based-image-segmentation

利用PCA和模糊C均值相结合的方法实现图象的聚类(Using PCA and fuzzy C-means method of combining images to achieve the clustering)

用于无参考帧图像质量评价的MATLAB程序，运行程序为example，输出图像的客观分值。(This is the matlab code of no-reference image qualituy assessment in space domain, th result ofthe program is the object acore of the image.)

基于核的相关滤波跟踪方法，最新的，TPMAI上的文章，速度超级快！(This MATLAB code implements a simple tracking pipeline based on the Kernelized Correlation Filter (KCF), and Dual Correlation Filter (DCF).)

小波方法的多焦点图像融合，用的融合规则为Yong Yang：A Novel DWT Based Multi-focus Image Fusion Method的方法(Wavelet method for multi-focus image fusion, the fusion rules: A Novel DWT Based Multi-focus Image Fusion Method method Yong Yang,)

sample illust back image2 mask sample

基于空间几何约束的单目视觉物体测距 基于空间几何约束的单目视觉物体测距(Geometric constraints based on spatial objects ranging monocular vision Geometric constraints based on spatial objects ranging monocular vision)

目前MATLAB里边对于多点计算仿射矩阵普遍采用RANSAC法，但是比较麻烦计算量也相对较大，通过最小二乘法来进行仿射矩阵的估计能够大大提高该效率，所以奉上自己在实验室写的仿射矩阵估计函数，来弥补matlab函数库在这方面的不足。(The MATLAB inside for calculating affine matrix commonly used RANSAC method, but more trouble calculation is relatively large, estimated by the least squares method to the affine matrix can greatly improve the efficiency, so give yourself in laboratory to write the estimated affine matrix function, to compensate for the lack of MATLAB Library in this area.)

控制测量是测绘专业的基础课程，这个课件是武汉大学老师编的课件，很实用(Control measurements are mapping the professional foundation courses, this courseware is Wuhan University teachers series courseware, very practical)

直方图拉伸是通过对比度拉伸对直方图进行调整，从而“扩大”前景和背景灰度的差别，以达到增强对比度的目的(Histogram stretching histogram is adjusted by contrast stretching, thereby " expand" the difference between the foreground and background of gray, in order to achieve the purpose of enhancing the contrast)

以图像拼接目标为应用背景，对图像处理配准和融合的基本原理及相关算法进行研究；利用matlab对相关配准和融合算法进行实现并优化;并将配准和融合算法应用于图像拼接中（给定某个真实场景的一组局部图像，然后对这一组图像进行拼接，最终形成一个图像拼接系统）。要求配准和融合能单独进行工作，形成独立的程序(The basic principles and algorithms of image registration and fusion are studied with the image stitching target as the application background. MATLAB is used to implement and optimize the related registration and fusion algorithms, and the registration and fusion algorithms are applied to the image mosaics (given a set of local images of a real scene, and then to this group) The image is stitching to form an image mosaic system. Registration and fusion are required to work independently and form separate programs.)