Image Transform Gray (non

沃尔什（Walsh）变换是一种可分离变换，广泛应用于图像处理。本代码实现了图像Walsh变换，非常经典，带图片可测试.-Walsh (Walsh) is a separable transform transform, which are widely used in image processing. Implementation of the code of the image Walsh transform, very classic, with pictures can be tested.

里边包含OpenCV中文参考手册 OpenCV是Intel® 开源计算机视觉库。它由一系列 C 函数和少量 C++ 类构成，实现了图像处理和计算机视觉方面的很多通用算法。 -Chinese inside OpenCV reference manual contains the OpenCV is Intel ? Open Source Computer Vision Library. It consists of a series of C function and a small amount of C++ Category consists realize the image processing and computer vision aspects of many common algorithms.

curvelet变换贝叶斯估计方法，用于估计含噪声图像的噪声参数。再对图像进行去噪处理-curvelet transform Bayesian estimation methods used to estimate the image noise with noise parameters. Re-image de-noising processing

Visual C++ 数字图像处理典型算法及实现(2)-Visual C++ digital image processing algorithms and implementation of a typical (2)

Snake game using C Graphics

一种基于小波的图像融合算法。2004年的一篇文章。-Wavelet-based image fusion algorithm.

vc6.0下，检测图像形状的轮廓的面积和周长，图像格式必须为BMP格式。-vc6.0, the detection of the contour shape image of the area and perimeter, BMP image format must be the format.

《数字图像处理编程入门》，非常容易上手，文字后有现成的通过运行的程序，是清华一位博士写的-Introduction to digital image processing program, very easy, after the language has ready-made by running the procedure, a doctor is written by Tsinghua

This code implements the well-known Chan-Vese segmentation algorithm from the paper "Active Contours Without Edges." This technique deforms an initial curve so that it separates foreground from background based on the means of the two regions. The technique is very robust to initialization and gives very nice results when there is a difference between the foreground and background means. This code uses active contours and level sets in the implementation. It could also serve as a good framework for implementing all kinds of region-based active contour energies. 1.) Download 2.) Unzip 3.) Run >>region_seg_demo See this site for experiments, videos, and more information on segmentation, active contours, and level sets: [ http://www.shawnlankton.com/2007/05/active-contours/ ]