regiongrowing

CNN卷积神经网络，能以高速将图像精确到的分类，给力。(CNN convolutional neural network with high speed, accurate to classify images, awesome.)

该算法可以清楚的将雷达目标检测出来，去除旁瓣遮挡效应，提高雷达目标检测的分辨率。(The algorithm can clear the radar target detection out, remove side lobe barrier effect, to improve the resolution of the radar target detection.)

通过手动框选目标区域，然后进行自动跟踪，使用的算法是Camshift，自适应均值漂移(By manually selecting the target area, then automatic tracking, using the algorithm is Camshift, adaptive mean shift)

物理光学法+物理绕射计算远场RCS的程序代码，c++程序(Physical optics+ physicaldiffraction computing far-field RCS program code, c++ program)

说明：  去除图像中的横向条纹，能有效恢复出原始图像(remove images of horizontal stripes, can be effectively restored from the original image)

用C++编写的产生文章的程序，方便有需要的人(C generated articles prepared by the procedures that are accessible to people in need)

随着视频的播放进行眼球追踪，如果眼镜反光会影响正确率(eyeball tracking in video p.s. note that the reflection of glasses may influence the performance)

用于计算两幅图片之间的峰值信噪比，从而衡量图片重建质量(It used to calculate the peak signal to noise ratio between the two pictures, which measure the quality of the reconstructed image)

针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更 新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al- gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD)

无源双基地雷达直达波脉冲丢失与相位突变影响分析Passive bistatic radar direct wave pulse loss and phase change impact analysis(Passive bistatic radar direct wave pulse loss and phase change impact analysis)