CDD

特征提取是图像配准的重要步骤，使用Harris角点检测算法实现图像拼接。(Feature extraction is an important step in image registration, using Harris corner detection algorithm for image mosaic.)

读入人脸图像，根据图像的水平，垂直灰度积分情况，将人眼范围取出，背景可以较复杂。(Reading into the human face image, according to the image of horizontal, vertical gray points, which will remove the scope of the human eye, the background can be more complicated.)

利用奇异值分解（SUV）对图像信号分行降噪！(Singular value decomposition (SUV) of the image signal branch noise!)

混合高斯分布EM算法，可以算混合高斯分布的三个参数。混合高斯分布更接近系数分布。(mixed Gaussian distribution EM algorithm can calculate mixed Gaussian distribution of the three parameters. Mixed closer to the Gaussian distribution coefficient.)

关于图像分块压缩感知，及测量矩阵加权的三篇文章(Three articles on the image block compressed sensing, and measurement matrix weighted)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )

最小二乘图像影像匹配方法，一个很详细的源码例程，有过程有结果，希望对初学者有帮助。高斯解方程，以及最小二乘匹配，里面都很详细。(Squares image image matching method, a very detailed source code routines, the outcome of the process, I hope to help beginners. Gaussian solution of equations, and least squares matching, which is very detailed.)

说明：  这是冈萨雷斯经典教材数字图像处理（MATLAB版）的所有源代码，很辛苦才获得的(This is a classic textbook Gonzalez Digital Image Processing (MATLAB version) all the source code, it is hard before they are allowed to)

一些常见的图像处理方面的图像（尺寸不一）(Some common image processing aspects (different sizes))

python写的图像相似度算法。比较图像相似度，选出最相思的图片(python write the image similarity algorithm. Compare image similarity, image to select the most Acacia)