the source is based on an image processing camera auto

图像超分辨是目前国内外研究的热点，该算法主要用于光学图像的超分辨-Image super-resolution is the study of hot spots at home and abroad that the algorithm is mainly used in optical image of the super-resolution

基于对比度分割的图像处理，阈值的选取通常以产生最大对比度为准。-Segmentation based on the contrast of the image processing, the threshold is usually selected to produce, whichever is the greatest contrast.

对图像分块,计算每个块的均值和方差,并给出了结果的图象化表示,易于观察-Image sub-blocks, each block calculated the mean and variance, and gives the results of the image that is easy to observe

在MATLAB环境下，以上代码通过编译。P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理-In the MATLAB environment, the above code through the compiler. P0311: the use of Butterworth (Butterworth) low pass filter on the image noise by smoothing treatment P0312: the use of Butterworth (Butterworth) high-pass filter for sharpening images treatment

利用vc++对动态目标进行检测，也可配合摄像头使用-Using vc++ for dynamic detection of targets can also be used with the camera

霍夫变换可以进行边值提取功能，在数字图像处理上功能强大-hough

基于kmeans的图像分割算法，首先得到图像，再确定分类，并计算各分类的均值，从而得到各个像素的分类。-Kmeans-based image segmentation algorithm, first of all get the image, and then determine the classification, and calculate the various categories mean, and thus obtain the classification of each pixel.

连通区域标记程序,本程序使用了opencv中图像数据结构：IplImage。算法原理：首先进行第一次扫描，标记连通区域；然后对等价标记进行合并；最后进行第二次扫描，对等价标记进行重新标记。-regional connectivity marking procedures, the procedures for the use of the OpenCV Image data structure : IplImage. Algorithm tenets : first for the first time, scanning, marking regional connectivity; Then equivalent marker for the merger; the final for the second scan, equivalent to re-labeled markers.

特征点提取方法--SIFT的简化后的算法-Feature point extraction method--SIFT algorithm of the simplified

A fast Matlab Paint GUI that works similarly to the Windows Paint program (except for the ROI image