pf_tracking-(1)

这是一部关于非高斯噪声中信号检测与估计的经典书籍，springer出版社出版，作者是S Kassam(This is a classical book about signal detection in non-Gaussian noise, by S Kassam)

维纳滤波和均值滤波，及利用自适应维纳滤波的图像去噪MATLAB代码，效果优于维纳滤波(Using adaptive Wiener filtering for image denoising MATLAB code, the effect is better than Wiener filtering)

运动估计中的各种搜索方法的源代码，方便实现运动估计(Motion Estimation in a variety of search methods of the source code to facilitate the realization of motion estimation)

说明：  图像处理算法质量评估，图像结构相似度（ssim)评价的matlab实现，并附带原始论文pdf(This is an implementation of the algorithm for calculating the Structural SIMilarity (SSIM) index between two images. Please refer to the following paper: Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error measurement to structural similarity" IEEE Transactios on Image Processing, vol. 13, no. 1, Jan. 2004.)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)

图像去噪处理的TV全变分模型的Matlab代码实现(TV image denoising processing model of the entire variational Matlab code)

用matlab实现了暗通道图像增强，完整源代码，出自暗通道增强算法的提出者。(Dark-channel image enhancement, complete source code from the authors of the dark channel enhancement algorithms.)

说明：  使用tensorflow框架搭建神经网络，从单目图像中估计深度值(Using tensorflow framework to build a neural network to estimate depth from monocular images)

说明：  一些快速实现图像模糊增强的的demo，matlab源码。已经测试通过。(Some image blurring rapidly enhanced the demo, matlab source. Have the test.)

图像拼接 sift 特征点，两幅图像进行拼配 拼接，先找找出特征点匹配(The image stitching， sift feature points, two images blending splicing find someone to identify the characteristics of point matching)