enviread.m

一些基本的图像处理算法的matlab实现，包括边缘提取和roc分析等(some basic image processing algorithms to achieve Matlab, including edge detection and analysis roc)

该程序是一个抗打印扫描数字水印算法的仿真，其原理基于DCT域的数据分类，具有很好的效果。原理参考杨义先等编著的《数字水印理论与技术》，高教出版社。(a print-scane watermarking scheme simulation)

说明：  本程序基于Matlab,初步实现图像增强的基本操作,实现 图像明暗度调整， 图像旋转，更改颜色显示方式，直接灰度调整，图像求反，动态范围压缩，显示原始图像直方图，直方图均衡化，滤波增强等功能(This procedure based on Matlab, the initial realization of the basic operation of image enhancement, image brightness adjustment, image rotation, change the color display, direct gray-scale adjustment, for anti-image, dynamic range compression, display the original image histogram, histogram equalization , enhanced features such as filtering)

Image Inpainting for object removal project report

医学图像分割和偏移场矫正方法的matlab代码(the matlab code for medical image segmentation and bias correction)

图形裁剪，实现对画的线，多边形，交点进行剪裁，实现图形的规范化(Graphic cutting, to achieve the painting line, polygon, tailoring intersection, graphics standardization)

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)

阈值重心法实现光带中心线提取，可用于结构光扫描的模型建立，处理二值化图像等。(Threshold barycenter method is used to extract the center line of optical band. It can be used to model structured light scanning and process binary images.)

旋转图像回归，图像拍照时有角度，此程序是将图像置平。(Rotating image regression )

基于小波模极大值贝叶斯阈值算法，实现图像吐糟的功能，与其他去噪方法进行对比。(Based on wavelet modulus maxima Bayesian threshold algorithm, spit bad image features comparison with other denoising methods.)