TERCOM

基于mmdetection框架的深度学习目标检测框架(deep learning object detection based on mmdetection)

说明：  二维功率谱密度计算程序 使用傅里叶变换，可以计算功率谱密度(Two dimensional power spectral density calculation program using Fourier transform)

说明：  卷积神经网络用于两幅遥感图像或者红外和可见光图像的融合(For fusion of two remote sensing images or infrared and visible images)

将保存有灰度图像信息的txt文件转化生成灰度图片。 txt数据只能包含数据，数据用逗号或者空格隔开，所存数据个数应与所生成的图片大小相同。例：要还原的图片大小为640*480，那么txt文件中就应当有307200个数据。(The txt file with information of grayscale image is transformed into gray image. The TXT data can only contain data, separated by commas or spaces, and the number of data stored should be the same as the size of the generated image. Example: the size of the image to restore is 640*480, so there should be 307200 data in the txt file.)

convert bmp to rgb565(algorithm to handle all kinds of bmp to rgb565)

非刚性强壮点匹配图像配准。用于医学图像配准。thin plate splines robust point matching.(nonrigid strong point matching image registration. For the medical image registration. Thin plate spline robust point matching.)

说明：  给出数字图像处理的，程序MATLAB的原代码，可以直接用于实验与验证(Given digital image processing, the original code of MATLAB program, can be directly used for experiment and verification)

利用固定目标和运动目标之间速度的差别所引起的多普勒频移不同根据在动目标 显示和动目标检测中使用的各种滤波器去除固定杂波提取动目标的回波能够大大 改善在杂波背景下检测运动目标的能力仿真结果显示出很好的效果也给出了改善 因子与积累脉冲数间关系 (radar moving target simulation)

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.)

用matlab编程实现的POCS-TVM算法，重建了一幅大小180*180的Shepp-Logan头部模型图像，探测器个数260，投影角度为均匀发布在0-180度之间的60个角度。(The POCS-TVM algorithm based on MATLAB programming is used to reconstruct a Shepp-Logan head image with a size of 180*180. The number of detectors is 260, and the projection angle is 60 angles that are evenly distributed between 0-180 degrees.)