APGL

这是本人发表的目标跟踪方面论文使用的代码，是基于随机假设概率滤波的多目标跟踪算法。(This is the code used by the target tracking paper I published, filter multi-target tracking algorithm based on the probability of a random assumption.)

图像巴特沃斯陷波器，实现了简单的巴特沃斯陷波器滤除图像的某些频率的干扰(Image Butterworth notch filter, to achieve a simple Butterworth notch filter to filter out images of certain frequency interference)

FCM源代码，专门用于图像分割的，速度很快(FCM source code, specifically for image segmentation, very fast)

说明：  基于光流法的运动目标检测 也可用于流体力学运动检测(Optical flow method based on the motion detection Motion detection can also be used for fluid dynamics)

说明：  针对一维最大类间方差算法(1-Otsu)抗噪性能较低、二维最大类间方差算法(2-Otsu)计算复杂度高、实时性差的问题,提出一种基于改进的萤火虫算法(FA)优化二维Otsu图像分割算法(FA-2-Otsu).(In order to solve the problems of low anti noise performance of 1-otsu, high computational complexity and poor real-time performance of 2-otsu, an improved firefly algorithm (FA) is proposed to optimize the 2-otsu image segmentation algorithm (fa-2-otsu).)

实现了三种图像匹配算法 1：归一化互相关匹配算法 2：基于Hausdorff距离的图像匹配算法 3：图像不变矩匹配算法(Implements three image matching algorithm 1: normalized cross correlation matching algorithm 2: image matching algorithm based on Hausdorff distance 3: The image matching algorithm invariant moments)

自行设计的概率密度函数统计方法，代替ksdensity函数(Probability density function of self-designed statistical methods, instead of ksdensity function)

论文《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》提出的算法代码(algorithm code of pape《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》)

说明：  最二小乘影像匹配，精度可以达到0.01个像素，也可以最二小乘影像模板匹配。经过修改后可以直接用，只要调用一个函数就搞定，函数参数的说明很清楚，绝对不会有任何困难，非常好用。(Most two Theravada image matching accuracy can reach 0.01 pixel images can also be the most two Theravada template matching. After modifications can be directly used, as long as is you call a function, function parameters, the description is clear and will not have any difficulties, very easy to use.)

自己编的求图像熵值的小程序，用来理解熵的含义和概念。(Own image for the entropy of small procedures, used to understand the meaning and concept of entropy.)