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西电许录平数字图像处理课件及习题解析，部分实验(Digital Image Processing PPT)

一个人体运动识别跟踪的示例程序，里面附带了一个运动视频，运行run.m文件。程序里包含了轮廓提取，跟踪算法，很好的tracking学习程序(A human motion recognition tracking sample program, which comes with a sports video, to run run.m file. The program includes a contour extraction and tracking algorithm, good tracking learning program)

像素与图像基本指标—彩色图像的基本信息、像素颜色值、图像的大小、矩阵形式等、对灰度图像计算有关统计参数：（1）图像的大小；（2）图像的灰度平均值；（3）图像的自协方差；（4）图像的灰度标准差、对图像进行45度，19度，98度等任意角度的旋转，并计算原图与旋转后图像的相关系数和协方差矩阵(Pixel and Basic Index of Image)

DISKREET: FOR CHANGING DISKREET LEVEL OF AN IMAGE

针对10个手写数字的识别问题，设计了一个BP神经网络，使它能够正确识别10个数字。(Against the 10 handwritten numeral recognition problem, a BP neural network is designed so that it can correctly identify the 10 digits.)

利用matlab编程技术将灰度图像归一化到0-255范围内(Normalize the image to 0-255)

采用快速简单的投影法和差影法实现条烟的缺陷检测(Fast simple video projection method and differential method to achieve Article smoke Defect Detection)

经典的Tarel去雾算法，可用于图像去雾的指标性能对比。(It is the classical dehazing algorithm, and it is can be used comparison with other algorithms.)

说明：  使用gpu、cpu并行进行sift算子计算匹配，能够在原来的基础上加速处理，但对显卡要求较高，具体环境配置使用方法可以参照mannual(SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors. SiftGPU is inspired by Andrea Vedaldi s sift++[2] and Sudipta N Sinha et al s GPU-SIFT[4] . Many parameters of sift++ ( for example, number of octaves, number of DOG levels, edge threshold, etc) are also available in SiftGPU. The shader programs are dynamically generated according to the parameters that user specified. SiftGPU also includes a GPU exhaustive/guided sift matcher SiftMatchGPU. It basically multiplies the descriptor matrix on GPU and find closest feature matches on GPU. Both GLSL and CUDA implementations are provided. )

说明：  该程序为小波图像去噪的matlab原代码，内容很丰富，大家可以共享(The procedure for the wavelet image denoising matlab source code, content is very rich, we can all share the)