zidianbijiao

基于Hilbert变换的相位差测量法分析及改进 (Based on the analysis phase measurement and improvement of the Hilbert transform)

图像读取与显示，图像二值化，边缘检测，边缘追踪(Read and display image, image binarization, edge detection, edge tracking)

rcmc: 距离徙动算法.SAR多点目标成像算法。含主瓣宽度和积分旁瓣比的求解。(rcmc: range migration algorithm. SAR multi-point target imaging algorithms. Including the main lobe width and sidelobe ratio integral solving.)

说明：  实现了双线性插值、三次样条插值、B样条插值和最大阶次优化差值等传统多项式图像插值办法(Traditional polynomial image interpolation methods such as bilinear interpolation, cubic spline interpolation, B spline interpolation and maximum order optimization difference are realized.)

用CPHD的方法实现多目标跟踪，及对CPHD性能的检测。(With CPHD method to achieve multi-target tracking, and performance testing for CPHD.)

说明：  傅里叶谱与频域低通滤波 (a)从图书网站下载图4.41(a)并计算其(居中)傅里叶谱。(b)显示频谱。(c)在等式(4.8-7)中实现高斯低通滤波器。您必须能够指定结果2D函数的大小，M x N。此外，您必须能够指定高斯函数的中心位置。(d)从图书网站下载图4.41(a)，并对其进行低通滤波，以复制图4.48中的结果。(Fourier Spectrum and Lowpass Filtering in Frequency Domain (a) Download Fig. 4.41(a) from the book web site and compute its (centered) Fourier spectrum. (b) Display the spectrum. (c) Implement the Gaussian lowpass filter in Eq. (4.8-7). You must be able to specify the size, M x N, of the resulting 2D function. In addition, you must be able to specify the location of the center of the Gaussian function. (d) Download Fig. 4.41(a) from the book web site and lowpass filter it to duplicate the results in Fig. 4.48.)

在高斯混合噪声背景下实现SLIM谱估计算法和l1范数SLIM谱估计法，并在-5到15的信噪比条件与CRLB对比均方频率误差(the paper achieves the SLIM spectral estimation algorithm and l1-SLIM spectral estimation method under the Gaussian mixture background noise,then compares the mean square frequency error with CRLB under SNR from-5 to 15 )

多目标检测与跟踪算法的实现，matlab程序，各个函数分开写的，便于调用(Many target detection and tracking algorithm, the realization of the matlab, each function, easy to call the write it separately )

ccd图像检测程序。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。(ccd image detection program. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .)

【高斯核函数改进 参考价值1】LBF活动轮廓模型的改进.pdf【高斯核函数的改进 参考价值5】单核和多核相关向量机的比较研究.pdf([Gaussian kernel improved reference value 1] .pdf LBF improved active contour models comparative study [.pdf Gaussian kernel improvements reference 5] single and multi-core related vector machine)