deeplab_v3-master

基于小波特征提取的图像匹配matlab程序，将图像进行二维小波变换，提取概貌系数，并去掉对特征影响不大的系数(Wavelet feature extracting based image matching)

说明：  基于matlab平台计算一副图像的信息熵(Calculate the entropy of an iamge using matlab)

识别结果详见下图，识别图像不错的例子

BSCB模型用于图像修复，模仿人工修复的过程，利用PDE的方式(BSCB model for image restoration, to imitate the artificial restoration process, the use of PDE way)

说明：  应用条件随机场进行图像分割 使用方法：将pydensecrf-py27或pydensecrf-py35重命名为pydensecrf，放入C:Program FilesAnaconda3Libsite-packages 运行：python inference.py im1.png anno1.png out.png(Renameing the file "pydensecrf-py27" or "pydensecrf-py35" to the new name "pydensecrf" Puting this file "pydensecrf" in this directory "C:Program FilesAnaconda3Libsite-packages" cd examples/ python inference.py im1.png anno1.png out.png)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

根据GetVersionEx获取版本ID获取系统名称(According GetVersionEx version ID for the system to obtain the name of)

用c#和emgucv实现了1.显示图像的直方图，2.直方图均衡化，3.中值滤波，4.sobel算子，roberts算子和Prewitt算子的边缘提取。各算法均自己实现不是调用函数。但是读图片的信息是用的emgucv。希望和同样刚接触emgucv的同学共同进步(With c# and emgucv achieve a 1 shows a histogram of the image, 2. Histogram equalization, 3 median filter, 4.sobel operator, edge roberts operator and Prewitt operator extraction. Various algorithms to achieve their own instead of calling a function. But reading the image information is used emgucv. The same hopes and common progress of students new to emgucv)

ISAR点目标RD成像算法,距离向包络对齐，多普勒中心相位补偿(Algorithm for ISAR point target imaging)

IDL环境下的EVF矢量数据创建，代码清晰。(IDL environment EVF vector data creation, code clarity.)