phasehaning

完成了对车道线进行了识别，主要流程为灰度化，边缘检测，hough变换。(We completed the lane line identification, the main process of graying, edge detection, hough transform.)

用matlab实现人眼定位的程序 ，包括滤波、阈值分割、人眼粗定位、精确定位等。(Using matlab realize the human eye positioning procedures, including filtering, threshold segmentation, the human eye coarse positioning, precise positioning.)

用于图像处理中的感兴趣区域的提取，以便对物体进行识别(extract the ROI in image process)

2012年的压缩感知跟踪算法，修改了部分程序源码，可以运行。(2012 of compressed sensing tracking algorithm, modify some program source code, you can run.)

一些matlab图像图像处理例程,骨架,灰度图像梯度,凸壳,细化.(Some image image processing matlab routines, skeleton, grayscale gradient, convex hull, thinning.)

孔径雷达图像固有的相干斑噪声严重降低了图像的可解译程度，影响了后续目标检测、分类和识别 等应用。因此，SAR图像的相干斑抑制问题一直是SAR图像应用的重要课题之一。一个理想的去斑算法应该在平 滑的同时保持图像的边缘等细节不受损失，目前存在各种各样的算法，但没有一种方法能够完美的满足这一要求。 本文对SAR图像的相干斑抑制问题进行了全面系统的研究，分析了相干斑的形成原因，总结了目前存在的相干斑 抑制算法的主要思路，介绍了具有代表性的算法，并对各种算法的性能进行了定性分析和比较，给出了去斑算法定 量评估方法(The inherent speckle noise of the aperture radar image seriously reduces the degree of interpretation of the image, and affects the detection, classification and recognition of the subsequent targets. And other applications. Therefore, the problem of speckle suppression in SAR images has been one of the most important topics in the application of SAR images. An ideal speckle algorithm should be flat At the same time, the details such as edges of images are not lost. There are various algorithms at present, but none of them can satisfy this requirement perfectly.)

该函数用来实现快速离散余弦变换。该函数利用2N点的快速付立叶变换来实现离散余弦变换(This function is used to implement fast discrete cosine transform. 2N points of the function using the fast Fourier transform to achieve the discrete cosine transform)

说明：  数字图像处理常用程序，包括图像读取、显示、详细信息，对图像文件格式转换，RGB分量显示，索引图像、伪彩色图像、真彩色图像显示，灰度直方图处理，图像灰度变换，均衡化处理，图像加噪声处理，均值滤波、中值滤波，图像加减乘除运算，图像放大，插值拟合，旋转，多种边缘检测方法，高通滤波，低通滤波，带通滤波，维纳滤波，运动模糊等处理。(Common digital image processing programs, including image reading, display, detailed information, image file format conversion, RGB component display, index image, pseudo color image, true color image display, gray histogram processing, image gray transformation, equalization processing, image plus noise processing, mean filtering, median filtering, image plus, subtraction, multiplication and division, image amplification, interpolation Fitting, rotation, multiple edge detection methods, high pass filtering, low-pass filtering, band-pass filtering, Wiener filtering, motion blur and other processing.)

人脸检测与跟踪，我的毕业论文，使用我自己改进的ADABOOST和CAMSHIFT算法,附带我的毕业论文,opencv1.0或以上自己配置(face detection use adaboost and camshift algorithm，relevant paper enclosed，OPENCV1.0 is necessary)

用Matlab实现的Canny边缘检测算法，压缩文件中附有一张实验图片(Using Matlab realize the Canny edge detection algorithm, compressed file attached to an experimental image)