fog-enhancement

任意位巴克码的匹配滤波以及模糊函数matlab源码(Any bit Barker code matched filter and ambiguity function matlab source code)

图像融合质量评价指标，包含灰度值，平均梯度，光谱扭曲程度，SSIM，PSNR，MSE等等。(Image fusion quality uation, including gray value, average gradient, spectral distortion degree, SSIM, PSNR, MSE, and so on.)

重要的纹理分割分类基础程序，可以进行更深入的探讨和优化，应用于遥感影像中。(Important basis for classification of texture segmentation procedure can be carried out more in-depth exploration and optimization, application of remote sensing images.)

Visual C++下的小波变换，小波分解与重构，加入噪声分析，显示分解和重构图形。(Wavelets for data encode and uncode, the figures would be shown.)

数字图像隐藏及提取研究分析论文、文献等。主要研究算法为LSB算法和DCT奇偶量化、DCT均值量化。(Digital Image Information Hiding and Extraction of analytical papers, literature. The main algorithm for the LSB algorithm and DCT parity quantization, DCT mean quantization.)

数学形态滤波。包括打开，滤波，处理，去噪等一系列功能。代码实验无误(Mathematical morphology filtering. A series of functions, including open, filtering, processing, denoising. Code experiment is correct)

利用surf算法,来实现图像间的拼接,并可将其推广为多幅图之间的拼接融合。(Realization of two images splicing)

多幅图像拼接matlab实现 sift特征提取、描述、匹配、RANSAC、仿射变换(Multiple image mosaics, MATLAB, SIFT feature extraction, description, matching, RANSAC, affine transformation)

用lbp实现纹理特征提取，并分类说明: 一共有三个m文件，一个是lbp.m, 存放主要的lbp算法， 一个是getmapping,用以做算法的辅助函数， 一个是lbptest.m,存放着测试代码。 这三个文件需要放到同一个文件夹，并在文件夹中添加相应的图片， 具体的图片名字见lbptest.m的代码，运行lbptest.m可以查看结果。代码最后给出效果图 这三个文件是最传统的LBP方法，有256种。(With lbp achieve texture feature extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

关于高光谱图像的图像处理技术，RX异常检测技术，代码功能强大，且代码注释很多，对学习很有帮助。(Hyperspectral image on image processing techniques, RX Anomaly Detection technology, powerful code feature, and many code comments, learning helpful.)