MRF-SAR-segment

在计算机视觉领域一种非盲去模糊的方法代码(A non-blind deblurring method code in the field of computer vision)

说明：  图像拼接 采用SIFT+RANSAC的特征匹配方法实现图像拼接(Image mosaic is realized by SIFT + RANSAC feature matching method)

实现对灰度图像的哈夫曼编码，对于其他图像，也可以类似的完成。(Realize grayscale images of hoffmann coding, for other image, also can be similar to the finish.)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)

这是一个关于基于方向谷形检测的静脉纹路分割的MATLAB程序代码，(Vein vein segmentation based on directional valley detection)

daisy是08年新提出来的特征描述符算法，常用在图像匹配等领域中。文件包含算法的PDF文档和算法提出者编写的相应matlab程序，大家可以根据自己的需要来利用。(A Fast Local Descriptor for Dense Matching，2008.)

运用harr特征+SRC（稀疏表示）分类实现的一种车辆检测方法，文件中提供了训练和测试车辆图片。由于时间原因，所用haar特征没有优化，维度过高，导致滑窗框图过慢，本代码只输出效果统计数据，以供大家参考学习稀疏表示在车辆检测中的应用。(Using harr feature+SRC (sparse representation) classification to achieve a vehicle detection method, the paper provides a training and test vehicle picture. Due to time reasons, the use of haar feature is not optimized, high dimension, resulting in sliding sash figure is too slow, the effect of the code only output statistics for your reference learning sparse representation in the vehicle detection.)

用matlab编写的图像恢复程序，实现压缩后图像的恢复()

用matlab画几个六边形。。。。。。。。。。。。。(Draw a few hexagons with MATLAB)

说明：  开源图形处理工具，可以处理图象，显示，投影转换，栅格和矢量数据处理(Open source graphics tool that can handle images, display, projection conversion, raster and vector data processing)