region_growing

此算法为基于k-means聚类的非局部均值快速去噪算法，方法便捷有效，可保持边缘信息(this is a fast edge-preserving denoising method based on non-local means method with k-means clustering)

可以打开大部分图片格式包括bmp、jpg等，并对其进行图片的基本处理包括翻转、镜像、傅里叶变换、直方图统计及均衡化、锐化、柔化、加椒盐或高斯噪声、中值滤波、Sobel边缘检测、高斯边缘检测、灰度阀值边缘检测、区域生长、旋转、缩放等操作(Can open most image formats including bmp, jpg, etc., and its basic image processing including flip, mirror, Fourier transform, histogram equalization statistics and, sharpen, soften, add salt and pepper or gaussian noise , median filtering, Sobel edge detection, Gaussian edge detection, gray level threshold edge detection, region growing, rotation, scaling and other operations)

经典的图像处理常用图片，包括Lina，Barbana, Cameraman(Classic image processing commonly used pictures, including Lina, Barbana, Cameraman)

快速TV算法用于图像去模糊、图像去噪等，其中TV模式包括两种(TV went fast algorithm for image blur, image denoising, which includes two TV mode)

数字图像处理的基础知识学习 涵盖源代码，有助于提高编程(digital image processing )

活动目标检测源码,用混合高斯算法编写，适用于复杂场景视频监控(alive target detection，used in GMM algorithm)

说明：  使用Harris角点检测器查找特征。再使用SIFT描述符并匹配两个图像之间的特征描述符。使用RANSAC执行单应。最后把图像包起来缝合。(Use Harris corner detector to find features. Sift descriptors are then used to match the feature descriptors between the two images. Use RANSAC to perform single response. Finally, the image is wrapped and stitched.)

这个是图像处理中的hough变换的C++源代码，工需要的同学参考学习。(This is the image processing hough transform C++ source code, engineering students need to learn.)

多分辨率灰度和旋转不变纹理分类与定位二进制模式(multiresolution gray scale and rotation invariant texture classification with location binary patterns )

利用ADMM和小波进行图像恢复 使用ADMM算法的图像恢复模型，并用到了增广拉格朗日函数和快速傅里叶函数(Using ADMM and wavelet to restore image, using ADMM algorithm to restore image model, and using augmented Lagrange function and fast Fourier function.)