imageMosaic

本文实现了Retinex算法，支持对图像的去雾灯操作，是一种图像增强的方法。(this paper present a new image strength method-Retinex impliment by opencv)

说明：  采用基于信道非均匀性校正改进的RLS算法实现对探测器的非均匀性校正(An improved RLS algorithm based on channel nonuniformity correction is used to correct the nonuniformity of detector.)

C# 拖拽截图（拖拽拉伸图片选框）

Lucy Richardson algorithm for image restoration

说明：  基于matlab的多帧图像超分辨重建。可以自行下载下来直接运行。(Multi frame image super-resolution reconstruction based on MATLAB.)

基于IBP算法的超分辨率图像重建，原理讲得十分清楚。(Super-resolution image reconstruction based on IBP algorithm. The principle is very clear.)

将处理过的二进制比特流写入图像，保存显示 (The treated binary bit stream to write the image )

时频峰值滤波（TFPF）算法是一种非常有效的去噪方法(TFPF is a effective method.)

在张正友的基于平面方格的摄象机标定中,单应矩阵是关键的一步,本程序是效率精度比较高的源码(Zhang is the Friends of the plane on the box camera calibration alone should matrix is a crucial step, The procedure is relatively high efficiency accuracy of source)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)