Estimation-master

第27章 透明位图背景上的滚动字幕实例该程序可以方便实现字幕的滚动效果，程序简单易懂(transparent bitmap on the background of rolling subtitles examples of the procedures to facilitate the achievement of subtitles rolling results, procedures simplified)

最大类间方差法图像阈值分割，基于matlab平台，适用于一维二维图像分割(Otsu method of image segmentation, based on matlab platform for one-dimensional two-dimensional image segmentation)

对话框以及树控件的描述及应用,很值得初学者学习，代码可以直接运行(Dialog boxes, and a description of the tree control and application, it is worth learning for beginners, the code can be run directly)

说明：  遥感图像运用6S工具来进行大气辐射校正处理(Atmospheric Radiation Correction Processing Using 6S Tool for Remote Sensing Images)

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：  几种常用的SAR图像滤波程序：初值滤波、中值滤波、维纳滤波、Lee滤波、kuan滤波等(some common filter program of SAR image,such as Lee filter,kuan filter.)

这个程序是马尔可夫的图像分割程序 对于初学者学习马尔可夫分割图像有帮助(This program is a Markov image segmentation program for beginners to learn Markov image segmentation helpful)

focuss算法 关于图像稀疏性分解中字典学习的经典算法 和大家一同分享 (focuss algorithm on the sparse image decomposition in the dictionary of the classical learning algorithm and we share)

此程序给出了如何对一个二维函数进行高精度高斯积分的实例。(This program shows how to function on a two-dimensional Gaussian integral precision instance.)

cvpr2012_oral On Multiple Foreground Cosegmentation(In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo sets where a finite number of K foregrounds of interest repeatedly occur over the entire photo set, but only an unknown subset of them is presented in each image. This contrasts the classical cosegmentation problem dealt with by most existing algorithms, which assume a much simpler but less realistic setting where the same set of foregrounds recurs in every image. We propose a novel optimization method for MFC, which makes no assumption on foreground configurations and does not suffer from the aforementioned limitation, while still leverages all the benefits of having co-occurring or (partially) recurring contents across images. Our method builds on an iterative scheme that alternates between a foreground modeling module and a region assignment module, both highly efficient and scalable. In part)