数字水印

说明：  车牌识别，图像分割出车牌，然后进行具体识别，matlab源代码(vehicle license plate recognition)

利用matlab对多光谱遥感影像进行水体指数（ndwi）以及植被指数（ndvi）提取(Extraction of Water body Index (ndwi) and vegetation Index (ndvi) from Multispectral remote Sensing Images by matlab)

线性CCD大津动态自适应阈值二值化源程序(Linear CCD dynamic adaptive threshold binarization dajin source program)

基于SUFT的特征提取与匹配，内涵详细的文档说明，很好的实现了特征提取与匹配，该方法较基本的SIFT有很大的提高(Extraction and matching of features based on SUFT, detailed content of the documentation, very good realization of the feature extraction and matching, SIFT the method is basic is greatly improved)

对灰度图像进行水平投影、垂直投影、对角投影其中对角投影是自己编的，已经运行过的(hsdbjhcbj kdjnkdj dhcnkujfhk )

FISM——结构相似度，它的功能为评价图像去噪效果，值越接近1，去噪结果越好。(FISM-- structural similarity, it functions is for the evaluation of image denoising effect, closer the value is to 1, better is the denoising results.)

说明：  opencv基础教程，对于初学者来说是个不错的选择。(opencv basic tutorial for beginners is a good choice.)

说明：  对图像提取同名点，并根据同名点建立delaunay三角网，后续可进行图像配准，或根据三角网进行控制点筛选(The same name points are extracted from the image, and the Delaunay triangulation network is established according to the same name points. The image registration can be carried out later, or the control points can be selected according to the triangulation network)

基于分数阶微分的图像增强技术，代码可以根据图像的梯度信息，更好地增强图像的高频部分，非线性地保留低频部分。(Fractional differential enhancement technology-based image code according to the gradient information of the image can better enhance the high frequency part of the image, to retain the low-frequency part of the non-linear.)

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. )