matlab图像运算

聚束SAR极坐标格式算法，包括dechirp处理以及距离向插值和方位向插值(Spotlight SAR polar format algorithm, including dechirp processing and distance and azimuth to the interpolation Interpolation)

说明：  一个立体系统相机标定，立体图像校正以及三维三角测量的多功能matlab工具箱。压缩包中包括一个PDF说明文档，和一个带有实验用图像的matlab程序压缩包。(A three-dimensional system, camera calibration, stereo image correction, as well as three-dimensional triangulation of multi-function matlab toolbox. Compressed package includes a PDF documentation, and one with an experimental image compression package matlab program.)

基于CFA（颜色滤波阵列）插值检测的图像篡改检测程序(Image tamper detection based on CFA (color filter array) interpolation detecting.)

平台基于visual studio2015，使用opencv函数实现双边滤波，进行图像处理(bilateral Filter based on opencv)

萤火虫算法 GSO算法用matlab编程实现(Firefly algorithm GSO algorithm using matlab programming)

Criminisi方法修复灰度图像（单通道）图像(Criminisi algorithm for gray image or single channel image )

C# 远程打码 实例项目源码

连接边缘算法提取的孤立点，实现图像边缘连接(link the point to get edges in the image )

考虑雨衰 阴影 和多径影响，可直接计算得到多重分形谱,非归零型差分相位调制信号建模与仿真分析 。( Consider shadow rain attenuation and multipath effects It can be directly calculated multi-fractal spectrum, NRZ type differential phase modulation signal modeling and simulation analysis.)

提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向 异性扩散（P-M扩散）两者的优点。通过P-范数方法选择合适的梯度阈值K，P-M扩散过程通过处理经过Curvelet 变换得到的图像的不同尺度的Curvelet 系数矩阵，实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。 实验表明，新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应，同时更好地保留图像的纹理和细节。 关键词：图像去噪算法；各向异性扩散；Curvelet 变换；P-M 扩散(Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed, which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.)