c1700-ios

一个颜色直方图的matlab源码，备注非常详细，可以实现(A color histogram matlab source code, notes are very detailed, can be achieved)

基于pcnn的图像融合及其相关的评价指标和融合结果(Image Fusion Based on PCNN， and Relevant uation index and the fusion results)

用MATLAB来实现简单图像特征点提取和匹配(Using MATLAB to implement a simple image feature extraction and matching)

九点标定halcon 代码，纯halcon代码未转换成其他语言(Marking machine image recognition Halcon code)

图像重采样，根据新旧图像像元大小的比例进行图像的重采样，(This function resamples the images at the new grid points defined by the new pixel sizes. It assumes that intensities are defined at the pixel centers)

包括canny，sobel，log等边缘检测的改进算法，使用效果良好(Including improved edge detection algorithms such as canny, sobel, log and so on, the application effect is good.)

虹膜识别的完整程序，有图片，有说明，可以用(The integrity of the iris recognition process, there are pictures, there are shows that can be used)

encryption and decryption of image using bit XOR..

这是冈萨雷斯版数字图像处理中的几个函数的实现，包括dftfilt, dftuv,hpfilter,imnoise2,improd,希望对你的学习有所帮助(This is the realization Gonzalez version Several digital image processing functions, including dftfilt, dftuv, hpfilter, imnoise2, improd, I hope to help you learn)

图像修复是图像处理的一个重要问题。这是一个困难的问题，同时填写在地区缺少图像信息的纹理和结构。以损坏的图像inpaint失踪的结构和纹理信息，基于小波分解的图像修补算法提出。首先损坏的图像分解成子图像和纹理结构，利用小波子图像转变。然后，地区结构中缺少的信息的子图像重建曲率驱动扩散（CDD），算法，而在同一区域的纹理子图像填写基于改进的纹理合成的典范 最后，恢复的图像，通过重组，结构和纹理恢复的结果。大量的实验表明，该算法可以快速，高效地恢复在同一时间的结构和纹理信息，视觉效果和峰值信噪比比（PSNR）比同类算法更好。(Image inpainting is an important problem image processing. It is a difficult problem to simultaneously fill-in the texture and structure in regions of missing image information. In order to inpaint the damaged image with both missing the structure and texture information, an image inpainting algorithm based on wavelet decomposition is presented. First the damaged image is decomposed into structure sub-image and texture sub-image using the wavelet transformation. Then, the sub-image with the region of missing information in the structure is reconstructed by Curvature-Driven Diffusions (CDD) algorithm, while the same region in the texture sub-image is filled-in with the improved texture synthesis based on exemplar Finally, the restored image is given by recombining the structure and texture restored results. A large number of experiments show that the proposed algorithm can quickly and efficiently restore the structure and texture information at the same time, and the visual eff)