VCPPqiangda-tuxiang-chuli

经典的数字图像处理的形态学处理，包含源代码(Digital image processing morphological processing)

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.)

计算机图像处理，MFC实现图像的直方图显示、直方图的均衡化，以及中值滤波等功能(Computer image processing, MFC histogram of image display, histogram equalization and median filter and other functions)

VTK读取BMP序列图片实现MC算法面绘制，并且将绘制结果保存为STL格式。(VTK read BMP image sequences to achieve MC surface rendering algorithm, and the results will be drawn saved as STL format.)

SURF 图像特征点快速提取法还有描述，可用于迅速匹配两张图片中的特征点(SURF image feature points extraction method also described fast, can be used to quickly match the image feature points in the two)

对视频进行基本的处理，例如载入视频，显示视频，控制播放(Basic video processing, such as loading the video, show video, control playback)

四叉树分割 opencv 编写 读入灰度图 进行递归分割(Quadtree segmentation opencv read into grayscale prepared for recursive partitioning)

Abstract—Noninvasive ultrasound imaging of carotid plaques allows for the development of plaque-image analysis methods associated with the risk of stroke. This paper presents several plaqueimage analysis methods that have been developed over the past years. The paper begins with a review of clinical methods for visual classification that have led to standardized methods for image acquisition, describes methods for image segmentation and denoizing, and provides an overview of the several texture-feature extraction and classification methods that have been applied. We provide a summary of emerging trends in 3-D imaging methods and plaque-motion analysis. Finally, we provide a discussion of the emerging trends and future directions in our concluding remarks.

基于遗传模拟退火和Otsu法的图像分割。采用一种基于模拟退火算法(SA)的混合遗传算法(GASA),来进行Otsu方法选择阈值，其中进行求解时是非线性的遗传算法（GA）的应用优化了求阈值过程，并尽可能地减少其运算量,而加入SA则避免了遗传算法(GA)常见的早熟收敛现象,从而实现有效简单的图像分割。 (adopt hybrid genetic algorithm(GASA) based on simulated annealing algorithm,choose threshold by Ostu method,which applicated the non-linear genetic algorithm(GA) allows us to optimize the process of threshold. And, where possible, to reduce the computation. in order to achieve effectivly and simply image segmentation. Combination SA is to avoid the common phenomenon about premature convergence in genetic algorithm (GA) to achieve a simple and effective image segmentation.)

meanshift 图像分割及平滑 包括meanshift的论文及ppt(Code for the Edge Detection and Image Segmentation system and the paper)