SAR_banmatu_ultimate_success

基于matlab的查找并剔除野值的程序,在信号处理与数据分析方面很好用(matlab find error)

运用最小二乘和一范数约束求解低分辨率多光谱图像和高分辨率全色图像融合成高分辨率多光谱图像，程序附带主流的图像融合评价标准，需要融合的图像，对比图像；以及附带程序所需的稀疏包(Using least squares and a norm constraint solving low-resolution multi-spectral image and panchromatic image fusion into a high-resolution multi-spectral images, the program comes with mainstream image fusion uation criteria require the integration of image contrast image and Sparse package comes with the program required)

对matlab中的GUI界面设计进行讲解并附有案例，例如如何进行界面菜单和控件设计，不同GUI之前函数传递，并讲解了如何调用自身函数(Matlab GUI interface design to explain the attached case, for example, how to interface menus and controls design, the different GUI function is passed before, and explain the how to call its own function)

说明：  使用gpu、cpu并行进行sift算子计算匹配，能够在原来的基础上加速处理，但对显卡要求较高，具体环境配置使用方法可以参照mannual(SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors. SiftGPU is inspired by Andrea Vedaldi s sift++[2] and Sudipta N Sinha et al s GPU-SIFT[4] . Many parameters of sift++ ( for example, number of octaves, number of DOG levels, edge threshold, etc) are also available in SiftGPU. The shader programs are dynamically generated according to the parameters that user specified. SiftGPU also includes a GPU exhaustive/guided sift matcher SiftMatchGPU. It basically multiplies the descriptor matrix on GPU and find closest feature matches on GPU. Both GLSL and CUDA implementations are provided. )

说明：  基于retinex算法对图像进行去雾算法(Image defogging algorithm based on retex algorithm)

半自动分割彩色图像的颜色相同区域，可以达到PS的魔棒效果(Semi-automatic segmentation of color images the same color region can reach the magic wand effect of PS)

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.)

图像处理效果评价,评价指标包括峰值信噪比，熵，以及均方误差，具体公式请参考相关文献(photo)

图像降噪、贝叶斯估计、盲源降噪,采用盲源方法进行噪声估计，再进行贝叶斯非局部均值降噪(Image denoising, Bias estimation and blind source noise，The blind source method for noise estimation, then the Bayes non local mean noise reduction)

Efficient Computation of Shortest Paths in Networks Using Particle Swarm Optimization and Noising Metaheuristics