Fire-detection-multiple-features

一种基于改进DRLSE的运动目标分割方法,为了得到精准、连续的运动目标轮廓，提出将帧间差分法和改进的距离规则水平集演化(DRLSE)方法结合应用于运动目标分割。(In order to get an accurate and continuous contour of moving target, a novel method to segment moving object by combining the frame difference and an improved distance regularized level set evolution (DRLSE) is proposed. )

this codes describe several kind of image filters

快速的Lee滤波算法，代码经过优化，修正和测试，能有效减少SAR图像中的斑点噪声。(Fast Lee filter algorithm, code optimized, modification and testing, can effectively reduce the SAR image speckle noise.)

程序实现了三种去噪算法：BLS-GSM/BM3D/NLM，评价指标为PSNR/SSIM.(Program implements three de-noising algorithm: BLS-GSM/BM3D/NLM, with evaluation of PSNR/SSIM.)

模糊图像去模糊处理，Amit等人发表的模糊核的估计算法，图像去模糊，得到清晰图像(image deblurring by Amit)

说明：  基于matlab 的图像除雾算法。可以很大程度去除雾霾对图像的影响。(Image Defogging Algorithm Based on matlab. The influence of smog on images can be removed to a great extent.)

本代码建立高斯混合模型(高斯多模型)(GMM)，将其用于计算机视觉领域的视频目标检测/视频监控/运动检测/运动目标检测/视频目标跟踪等相关应用中。(This code sets up Gaussian mixture model(Gaussion Mixture Model, GMM) with image sequences for the research and application field of computer vision, using GMM for visual object detection(video object detection), visual surveillance, motion detection, motion tracking, visual object tracking, video object tracking, etc.)

基于格子玻尔兹曼方法模拟泊肃叶流，边界条件用非平衡格式(Poiseuille flow based on the lattice Boltzmann method to simulate the boundary conditions with unbalanced format )

摄影测量中影像匹配的程序，选择左右影像，可直接显示匹配结果。程序用C#编写(Photogrammetry image matching procedures, C# Prepared)

说明：  在这个知识库中，图形信号处理的一些有趣的特性被表示出来。演示通过经典信号处理和图形信号处理对一维和二维欧几里得域信号应用低通滤波器，比较两种方法的结果。在此基础上，验证了图形信号处理的工作机制。此外，还描述了在非欧几里得域上滤波信号的示例。(In this repository, Some fascinating features of Graph Signal Processing were represented. Demos incudes applying a low-pass filter on both 1D and 2D euclidian domain signal by classical signal processing and also Graph signal processing to compare both results are the same. Within that way, we will validate the working mechanism of Graph Signal Processing. In addition to this, an example of filtering a signal on the non-euclidian domain was also represented.)