knife

这里包含了多种图像倾斜角度矫正的方法 其中有huogh变换 radon变换 还有常规的线性检测角度 然后矫正它(This contains a variety of image angle correction method which huogh transform the linear radon transform routine testing point of view there and then correct it)

图像修复是对图像中破损区域进行信息填充，以减少图像破损所带来的信息损失的过程。 传统的图像修复方法需要依赖图像的具体结构来制定相应的修复方法，压缩感知理论的提出，使得可以利 用信号的稀疏性来对图像进行修复。基于K 奇异值分解（KSVD）与形态学成分分析（MCA，Morphological Component Analysis）的图像修复方法首先采用形态学成分分析方法对破损图像进行特征分析，将其分解 为结构部分和纹理部分；然后基于学习型字典KSVD分别对这两部分进行过完备字典训练；最后利用训练得 到的字典实现对破损图像的修复。相比于传统的图像修复方法，该方法具有适应性强、修复效果好等优点(Image inpainting is to fill the missing data in corrupted images and thus to reduce the information loss of damaged image. Traditional inpainting algorithms are dependent on specific structure of target images compressive sensing theory makes is possible to realized image inpainting with signal sparsity. This paper proposes a novel inpainting algorithm based on KSVD and MCA algorithm, which first decomposes the image into texture part and structure part, and then trains the two dictionaries for these two parts with KSVD and reconstructs the original image with these two trained dictionaries. Experiment indicates that the proposed algorithm is of better adaptability and performance as compared with traditional algorithms.)

说明：  基于BoVW的图像特征提取，以及图像检索(Image feature extraction and image retrieval based on BoVW)

摄影测量的一个开源代码，内部含有后方交会、前方交会、相对定向、立体量测、像点匹配等功能源代码。(An Photogrametry open source project, including intersection, relative oriention, stereo measure, image matching source code.)

初步的代码，只保存边界的声波逆时偏移 RTM

Harris，SURF特征点提取匹配算法，两种算法实例比较(Harris, SURF feature point extraction matching algorithm compares two algorithms examples)

说明：  运行程序，得到不同伽马因子给图像的整体明暗程度带来的变化(Run the program to get the change of the overall brightness of the image with different gamma factors)

将原图与一幅模板图像进行计算相关 以图像显示相关函数(The original image and a template image to calculate correlation functions related to image display)

利用matlab，对图像进行高斯滤波，然后通过非极大值抑制，设置双阈值，实现图像边缘检测(Image edge detection)

本程序能够综合地实现图像边缘细化，而且程序够复杂。(This procedure can be integrated to achieve the Image Edge thinning, and the procedures complex enough.)