2014

文档介绍了大量离散实验数据的平滑滤波处理方法(Document describes a large number of discrete experimental data smoothing filter processing method)

hit-miss方法下的图像骨架提取，很好用(hit-miss method of image skeleton extraction, very good use)

先进行图像的预处理，采用中值滤波，梯度增强。基于边缘帧差法实现前景检测(first image preproceing，the median filtering，grdient enhancement。based on edge detection method of frame to realiase prospect)

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.)

文件中含有粒子滤波完整代码以及几种改进粒子滤波算法代码，运行主函数可以分别看到粒子滤波算法和改进后的算法运行效果，适合初学者学习应用(The file contains the complete code of particle filter and several improved particle filter algorithm code, run the main function algorithm performs the particle filter algorithm and the improved see respectively, suitable for beginners to learn to use )

训练了一个CNN模型用于土地资源分类，适用于遥感图像(A CNN model is trained for land use classification and is suitable for remote sensing images.)

图像处理（图像融合，图像加密等）的性能评价指标集包括：平均梯度，边缘强度，信息熵，灰度均值，标准差(均方差MSE)，均方根误差，峰值信噪比（psnr），空间频率(sf)，图像清晰度，互信息(mi)，结构相似性(ssim)，交叉熵(cross entropy)，相对标准差。(Image processing，average gradient, edge strength, information entropy, gray mean, standard deviation (variance (MSE), are root mean square error, peak signal to noise ratio (PSNR), spatial frequency (SF), the sharpness of the image, the mutual information (MI), similar to the structure of (SSIM) and cross entropy (cross entropy). The relative standard deviation)

image decomposition and reconstruction

基本图元绘制、计算机图形学上机实验报告、1，熟悉图形软件开发工具：VC++, OpenGL等； 2，设计、实现线段的DDA、Bresenham算法 3，设计、实现中点圆、中点椭圆生成算法； 4，设计、实现填充图元生成算法；(The basic primitive computer graphics, computer lab report 1, familiar with the graphics software development tools: vc++, OpenGL, etc. 2, design implementation DDA Bresenham algorithm of line 3, midpoint circle midpoint elliptical generation algorithm design implementation 4, primitive design to realize filling generation algorithm)

水平集代码和论文，图像分割,快速有效的图像分割方法(code and paper about level set,image segmentation)