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An efficient way of segmentation, grabcut matlab code. Segment by interaction with human can easy segment object, especially with rectangle

图像处理fuzzy C-means算法的源代码(Image processing fuzzy C-means algorithm source code)

brovery图像融合代码，效果比较好，还有两幅测试图像，一幅是高分辨率的全彩色图像，另一幅是多光谱图像(brovery image fusion code, the results were better. There are two test images, a high-resolution full-color images, the other is a multi-spectral image)

houph变换，通过梯度函数得到图像的梯度矩阵，通过检测圆检测眼睛位置。(houph transform, through the gradient function to be the image gradient matrix, circle detection by detecting the location of the eyes.)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

针对CT 医学图像和MR I 医学图像成像特点, 提出了基于快速整数提升小波变换的融合方法。在CT 和 MR I 两幅医学图像配准的前提下, 利用提升小波变换把图像分解成低频和高频子图像, 对于小波变换后的高频 子图像, 选择区域标准差大的作为融合后的子图像 对于低频子图像, 采用加权融合, 最后进行小波逆变换, 得到 融合后的图像, 并对融合后图像用信息熵、平均梯度、相关系数的指标进行评价。实验结果表明, 基于快速整数提 升小波变换融合中, 小波高低频系数采用不同的规则能够取得更好的融合效果, 其轮廓清晰。该算法能够提升融 合后的医学图像信息量, 同时有效地保护图像的细节信息, 在执行时间和图像质量上均优于普通小波算法。(A imed at the characterist ics of CT andMR Imedical images, a new image fu sion al2 go rithm based on the fast in t lif t ing w avelet t ran sfo rm s is p ropo sed. Two o riginal images are decompo sed by the fast in t lif t ing w avelet t ran sfo rm s. The fu sion ru le based on the max imum standard deviat ion value variance is u sed to fu se the h igh f requency sub2image, w h ile a w eigh t2 ed average fu sed ru le is app lied by coeff icien t s of the low f requency. F inally, the fu sion image is recon st ructed fo r perfo rm ing inverse fast in t lif t ing w avelet t ran sfo rm s. The fu sion image is evaluated by en t ropy, average gradien t, and co rrelat ion coeff icien t s. Experimen tal resu lt show s that the fu sion image hasmo re info rmat ion than o riginal images and imp roves the quali2 ty of o riginal images. M eanw h ile, the fu sion image p ro tect s detail characterist ics of the image, thu s the real2t ime p rocess and image qualit ies are w ell than tha)

利用matlab控制摄像头，对图像实时进行二值灰度处理(Using MATLAB to control the camera, the image is processed with two value gray in real time)

说明：  脆弱性数字水印能为多媒体内容完整性认证和篡改检测提供有效的解决方案。该文对用于图像认证的脆弱性数字水印技术的研究 现状、一般原理、基本特征、典型算法进行了综述(The vulnerability of digital watermark for the integrity of multimedia content authentication and tamper detection to provide an effective solution. The image authentication for the vulnerability of digital watermarking technology, research, general principles, basic features, typical algorithms are reviewed)

说明：  思想：把原始图的直方图变换为均匀分布的形式，这样就增加了灰度值的动态 范围从而达到增强图像整体对比度的效果。其优点是能自动地增强整个 图像的对比度。 1、对灰度图像进行直方图的均衡化处理，达到图像增强的目的。 2、利用平均滤波和中值滤波对图像进行平滑滤波。 3、利用拉普拉斯运算对图像进行锐化滤波。(Idea: transform the histogram of the original image into the form of uniform distribution, so as to increase the dynamic gray value Range to enhance the overall contrast of the image. Its advantage is that it can automatically enhance the contrast of the whole image. 1. The gray image is processed by histogram equalization to achieve the purpose of image enhancement. 2. Average filter and median filter are used to smooth the image. 3. Using Laplace operation to sharpen the image.)

数字图像处理中图像的增强方便的源代码，包括图像灰度修正，图像的平滑，中值滤波，图像的锐化，伪彩色和假彩色的增强等(Digital image processing image enhancement convenient source code, including the gray correction, image smoothing, median filtering, image sharpening, pseudo-color and false color enhancement, etc.)