sift

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)

说明：  利用大津算法对图片进行处理，得到满意的处理效果。(The image is processed by Otsu algorithm and satisfactory results are obtained.)

vc++ 数字图象处理 很好用我看了以后收益非浅希望大家喜欢(vc digital image processing with very good after I read greatly benefit hope you like)

一种基于non-sample的纹理合成demo，程序性能还有待优化，效果还不错.(texture synthesis demo.)

将一个图像的感兴趣区域替换到另一张图像的相同区域中(Will replace the region of interest of an image to another image of the same region of the)

内置虑镜功能，包括获取图像的属性，锐化，模糊，浮雕等功能． 可以缩放，优化图片．打开图片带预览功能,使用了gdiplus,能处理gif,bmp,jpg,png图片,处理速度也不错，呵呵,一直找图形格式转换的朋友就不需要东找西找了，它完全可以实现你的需求！ (Built-in lens into account features, including access to the properties of the image, sharpen, blur, emboss and other functions. Can be scaled to optimize picture. Open the image with the preview function, use the gdiplus, can handle gif, bmp, jpg, png images, the processing speed is not bad, huh, huh, graphic format conversion has been looking for friends do not need to look east and west, and it can achieve your needs!)

图像增强，包括图像的平滑、锐化、边缘识别等操作(Image enhancement, including image smoothing, sharpening, edge detection and other operations)

Camshift算法，即"Continuously Adaptive Mean-Shift"算法，是一种自适应的运动跟踪算法。它主要通过视频图像中运动物体的颜色信息来达到跟踪目的。(Camshift algorithm, namely " Continuously Adaptive Mean-Shift" algorithm is an adaptive motion tracking algorithm. It is primarily the color information of the object' s movement through the video images to achieve tracking purposes.)

说明：  基于Kmeans算法的图像分割，一般Kmeans是数据挖掘中用来聚类的，本试验利用图像中的灰度值作为Kmeans算法的原始点，进行图像分割(Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for Image Segmentation)

深度图像的快速实现增强的算法，效果非常好，但是速度很快(Quick to realize the depth of image enhancement algorithms, the effect is very good, but fast)