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用matlab仿真，研究不同阈值降噪后的效果，使用penalty阙值降噪后信号，使用Birge_Massart阙值降噪后信号，使用缺省阙值降噪后信号。(Using matlab simulation to study the different threshold noise reduction effect, the use of penalty threshold denoised signal after noise reduction using Birge_Massart threshold signal, use the default threshold signal after noise reduction.)

2、掌握Lee滤波与Refined-Lee滤波滤波效果ENL/ESI分析的原理及方法； 3、分析比较Lee滤波与Refined-Lee滤波的滤波性能； 4、分析滤波窗口与滤波效果的关系。 (2, master the principles and methods of filtering and Refined-Lee Lee filter filtering effect ENL/ESI analysis 3. Comparative analysis filtering performance Refined-Lee Lee filter and filter 4, analysis filtering window and filtering effect relationship.)

利用粒子群算法做的关于基于指数熵对数熵TSALLIS熵的多阈值的图像分割，内附无优化算法，可以做时间比较(Using particle swarm optimization to do on the entropy-based index of the number of entropy TSALLIS entropy of multi-threshold image segmentation, containing no optimization, can do more time)

说明：  用VC实现数字减影算法，通过模板匹配，再对两幅图像相减，即用盈片中减去蒙片，从而实现突出血管区域的目的。【源码加文档说明】(Using VC to achieve digital subtraction algorithm, template matching, and then the subtraction of two images, that the film with surplus minus mask, in order to achieve the purpose of highlighting vascular region. 【Source】 plus documented)

最大熵双阈值分割算法，基于遗传算法优化的快速最大熵双阈值分割算法。(Maximum Entropy Double Threshold Segmentation and Fast Maximum Entropy Double Threshold Segmentation Based on Genetic Algorithms.)

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.)

平时工作中常会遇到需要处理图片的工作，这个是判断并修改图片分辨率的python方法。(Usually work the Central Standing Committee met to deal with the work of the picture, this is a python method to determine and modify the image resolution.)

Metaface Learning for Sparse Fisher Discrimination Dictionary Learning for Sparse Representation

RMSHE算法（recursive mean-separate histogram equalization）。基本原理是将图像根据平均灰度进行分割，各部分分别进行直方图均衡。文件中包含RMSHE的matlab源代码，论文，以及输入图像(RMSHE algorithm (recursive mean-separate histogram equalization). The basic principle is that the image based on the average gray-scale is divided, each part respectively histogram equalization. File contains RMSHE matlab source code, papers, as well as the input image)

Kullback-Leibler Importance Estimation Procedure利用Matlab程序实现图像间KL散度的阈值分割(Kullback-Leibler Importance Estimation Procedure procedure using Matlab implementation KL divergence between the image of the threshold segmentation)