LBF

目标跟踪程序,使用matlab编写,采用CV模型,卡尔曼跟踪,有轨迹模拟,给出了跟踪的误差 目标跟踪,采用CV模型,卡尔曼滤波,给出模拟结果和跟踪结果,给出误差分析(Target tracking program, using matlab prepared, using the CV model, Kalman tracking, trajectory simulations have given a tracking error target tracking, using the CV model, Kalman filter, and track the results of the simulation results are given, error analysis is given)

雷达与红外目标跟踪融合的尝试，探讨中(Target tracking radar and infrared fusion attempts to explore in)

基于直方图的多阈值分割可以求出三个阈值，适合CT图像分割(Histogram-based multi-threshold segmentation can be obtained three threshold for CT image segmentation)

image processing application

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.)

图像重建算法当中的FDK、ART和TV算法，以及算法评估的SSIM和MSE的评估代码(FDK, ART and TV algorithms in image reconstruction algorithms, and the evaluation codes of SSM and MSE for algorithm evaluation)

canny算法分割，本算法通过canny对图像进行分割，并提取边缘。()

meanshift算法的python实现 + 图像化显示(meanshift with python)

采用matlab，代码经过修改，可以去除阴影，但还不能在实际应用中用，不过有一定的参考价值(Using matlab, the code has been modified to remove the shadow, but it can not be used in the actual application, but there is a certain reference value)

使用regionprops中BoundingBox功能对图片进行处理获得X,Y的坐标值以及长宽度(Use regionprops the BoundingBox of the image processing functions to obtain X, Y coordinate values and long-width)