Image-Impaint-Based-on-Curvelet

对一幅图片批量添加20个级别的噪声，支持添加高斯白噪声和椒盐噪声两种噪声。(Add a picture batch 20 levels of noise, two noise support the addition of white Gaussian noise and salt and pepper noise.)

经典的4种彩色图像分割方法：CSC.EGBIS.JSEG.Meanshift 的VC++实现；及相关英文文献。绝对值得拥有！哈哈...(The classic four kinds of color image segmentation method: CSC.EGBIS.JSEG.Meanshift of VC++ implementation and the relevant literature in English. Definitely worth having!ha ha ...)

YUV420p图像的融合渲染，支持任意位置的融合，并支持alpha的渲染(Fusion YUV420p image rendering, support converged anywhere and supports alpha rendering)

图像处理的查准率和查全率的代码，适合用于图像图像的检测，目标的检测的评估(Image processing precision and recall rate code)

模糊图像去模糊处理，Amit等人发表的模糊核的估计算法，图像去模糊，得到清晰图像(image deblurring by Amit)

说明：  相关图像算法包括大律法分割，梯度分割，分水岭分割，活动轮廓，最小生成树，相关基因算法(Great Law Segmentation, Gradient Segmentation, Watershed Segmentation, Active Contour, Minimum Spanning Tree, Related Gene Algorithms)

说明：  检测火灾，本课题为基于matlab的火灾检测识别，烟雾报警，火焰检测，通过几何参数判别，即面积增长率，角度等。完美运行。(Detection of fire, this topic is based on the MATLAB fire detection and recognition, smoke alarm, flame detection, through the geometric parameters, that is, area growth rate, angle and so on. Perfect operation.)

说明：  基于计算机断层扫描技术的正弦图，使用滤波反投影算法重建图像(filter back projection reconstruct)

主要思想是用meanshift算法跟踪目标，拖动矩形框选择目标模板，meanshift自动跟踪 本程序的主要缺陷体现在帧差法自动识别目标，这部分功能与上一个功能独立，可用可不用，用于自动识别目标，效果不是很好，主要体现在对图像视频的要求是 背景（目标以外的所有事物）不能动(The main idea is to use meanshift algorithm to track the target and drag a rectangle to select the target template, meanshift automatic tracking The main drawback of the program is reflected in the frame difference method automatically identifies the target, which is part of the function and one function independently, may or may not, be used to automatically identify the target, the effect is not very good, mainly reflected in the requirements of the video image is the background (target All things outside) can not move)

源码包括了常用的图像处理方法，代码详细，适合初学者(Source code, including the commonly used image processing method, the code in detail, suitable for beginners)