PSIR_ISIR_IRW

雷达探测开关，用于检测前方是否有移动的物体?(Radar detection switch for detecting whether there is in front of the moving object?)

对全息图进行卷积法的再现，利用matlab计算全息图模拟仿真(Reappearance of convolution method for hologram)

说明：  共享主成份尺度不变变换PCA-SIFT代码，用于SAR图像配准，希望对各位雷达爱好者和SAR工作者有用！(Principle component analysis, PCA- Scale invariant feature transform-SIFT used for SAR processing. )

Cohen类时频方法采用不同的核函数来抑制交叉项，本质上是在模糊域对信号进行低通滤波，其中典型的方法有Choi-Williams 分布和Cone-shaped 分布等。(The Cohen time frequency method uses different kernel functions to suppress the cross term, which is essentially a low pass filter for the signal in the fuzzy domain. The typical methods are Choi-Williams distribution and Cone-shaped distribution.)

针对电气设备同一场景的红外与可见光图像间一致特征难以提取和匹配的问题，提出了一种基于斜率一致性的配准方法。首先通过数学形态学方法分别提取红外与可见光图像的边缘，得到粗边缘图像；然后通过SURF算法提取两幅边缘图像的特征点，根据正确的匹配点对之间斜率一致性的先验知识，进行特征点匹配；最后通过最小二乘法求得仿射变换模型参数并实现两幅图像的配准。实验结果表明，该方法有效提高了匹配点对的正确率，能够对电气设备红外和可见光图像实现高精度的配准。(In this paper, a method based on slope consistency is proposed to solve the problem that the uniform features of infrared and visible images are difficult to extract and match. Firstly, the edges of infrared and visible images were extracted by mathematical morphology, and the rough edge images were obtained. Then, the feature points of two edge images were extracted by SURF algorithm, and the priori knowledge of slope consistency was obtained according to the correct matching point, and the feature points were matched. Finally, the model parameters of affine transformation are obtained by least square method and the registration of two images is realized. The experimental results show that this method can effectively improve the accuracy of matching points, and can realize high precision registration of infrared and visible images of electrical equipment.)

应用投影算法对TV模型快速求解，并将算法应用到图像去噪中(The projection algorithm is used to solve the TV model quickly, and the algorithm is applied to image denoising)

matlab　ＰＣＡ源代码 有中文注释(source code matlab PCA has Chinese Notes)

3D 点云建筑物分割代码3D 点云建筑物分割代码3D 点云建筑物分割代码(3D point cloud, buildign segmentation3D point cloud, buildign segmentation3D point cloud, buildign segmentation)

基于字典学习和矩阵低秩稀疏分解的SAR图像处理新方法，拓展了低秩稀疏分解的应用领域，有很好的应用前景。(Dictionary Learning and Low-rank Sparse Matrix Decomposition for Sparsity-driven SAR Image Reconstruction)

EM算法。问题背景是，有N条长为L的DNA序列，每条序列里面有一条长尾K的目标序列，但不知道他的位置，目标序列内的核苷酸服从foreground product multinomial distribution，非目标序列服从background multinomial distribution，改程序意在求解两种分布的参数。(EM algorithm. Background to the issue is that there are N pieces of length L of DNA sequences, each sequence which has a target sequence Nagao K, but do not know his position, the target nucleotide sequence within obedience foreground product multinomial distribution, non-target sequence obey background multinomial distribution, the program is intended to change the parameters in solving the two distributions.)