L2

图像处理中边缘提取几种方法的matlab代码(many edge extraction codes about image processing)

去噪算法matlab源码三合一，包含BLS-GSM，BM3D，NLM(Denosing algorithms 3 in 1, include BLS-GSM+ BM3D+ NLM)

图像的二值化，并对图像做膨胀，腐蚀，开、闭操作，以及细化处理等通过用matlab高级语言编写数字图像处理的一些基本算法程序(Binarization image, and image to do the expansion, corrosion, open and close operation, as well as refining processing through high-level language matlab digital image processing procedures for some of the basic algorithm)

Implementations of image processing algorithms(This project can be built by Visual Studio 2012. Project description file included. Currently it is for Windows only.)

基于光流法的二维单模态图像配准，能得到变形场(This will allow you to generate the deformation field needed for contour guided multi-modal image registration.)

使用python语言实现多张图像的拼接，并且处理拼接之后的裂缝和黑边。(Use python language to achieve splicing of multiple images, and deal with cracks and black edges after splicing.)

针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更 新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al- gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD)

一种基于SIFT的图像配准方法，目前使用最广泛的一种配准方法。性能优。(One kind SIFT image registration method based on the most widely used kind of registration method. Excellent performance.)

对车牌进行预处理（图像分割），然后进行文字识别(Pretreatment of the plate (image segmentation), and then proceed to character recognition)

扩散方程的MATLAB代码：可用于图像平滑、去噪、滤波及图像的边缘处理等(Diffusion equation of the MATLAB code: can be used for image smoothing, denoising, image filtering and edge treatment, such as)