K_MeansSeg

基于VisualC_和DCMTK的医学DICOM图像显示与调窗,同时在MFC 下完成鼠标拖动进行窗宽/窗位的调节(Medical image of DICOM VisualC_ and DCMTK display and window based on, at the same time in MFC complete the mouse to drag the window width/window regulator )

灰度数字图像增强处理,灰度数字图像增强处理,灰度数字图像增强处理,(Deal with gray-scale digital image enhancement)

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 ...)

小型图像处理平台，包括滤波，边缘提取，边缘优化以及图像匹配功能(Small image processing platform, including filtering, edge detection, edge optimization and image matching function)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

在visual c++中用分形完成的julia集,是分形的具体应用,对学分形的朋友应该有帮助(In the visual c++ Used to complete the julia fractal set, is the concrete application of the fractal, Friend of the credits should be shaped to help)

图像亮度和对比度调节，已验证，分别有亮度调节和对比度调节的调整框(Image brightness and contrast adjustment, has been verified, respectively, brightness adjustment and contrast ad)

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)

基于OpenCV实现的图像剪切，截取小软件，对学习OpenCV的朋友比较有帮助(OpenCV based on the realization of the image shear, the interception of a small software, to learning more OpenCV friends help)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)