hog-feature

说明：  Python 分水岭算法 用于图像分割等图像处理(Python watershed algorithm)

进行图像区域合并操作,能够较为有效，较好的进行图像合并(combine the image，very effcient)

MODIS图像批量镶嵌拼接方法（IDL/ENVI）(modis mosaic)

本实验要求编写一个计算压缩-解压缩图像的均方根误差、均方信噪比的程序。该程序是一个通用程序。编写程序产生图示的结果。使用上面的保真度准则程序计算可视信息的损失特性。(Prepared in this experiment, a calculation of compression- decompression of the root-mean-square error of image, mean square signal to noise ratio of the procedure. The procedure is a common procedure. Picture shows the preparation of the results of procedures. The use of the above criteria for the fidelity of calculated loss characteristics of visual information.)

Face recognition system based on Eigenface, written in Matlab, including the paper which has present the structure and each component in detail. Hope it will be useful!

本文件为一个可以实现自适应滤波算法的函数。在去噪等方面有这较好应用。(This document is an adaptive filtering algorithms to achieve the function. This application has a good de-noising and so on.)

运动模糊图像 图像复原 维纳滤波复原 逆滤波复原 VC++6.0程序 代码(Motion-blurred image restoration image restoration Wiener filtering inverse filtering to recover VC++ 6.0 code)

说明：  ：在深海采矿环境中超声波传输介质里存在着大量气泡、扰动沉积物、机械噪声等背景噪声与混响，导致有用信号与高 噪声信号迭加在一起，严重影响了测距精度。采用小波分析方法将超声回波信号进行3层小波分解，适当设置门限阈值对小波 系数进行处理，然后对信号进行重构，有效地抑制了信号中噪声对测量精度的影响。研究结果表明：小波方法有很好的降低回 波信号中噪声的效果，其测距精度高于自适应滤波去噪后的测距精度。(There are much background and mixture noise in the course of ultrasonic wave transmission under deep sea mining environment，such as air bubbles and disturbed sediment and mechanical noise．Because of these factors， the useful signals and the high noise signals are combined together，which seriously affects the distance measurement precision．Ultrasonic echo signals are decomposed into three layer wavelets，and a threshold is set to process the wavelet coeficients．Then the signals are reconstructed．Accordingly the influence of environment noise on distance measurement precision is effectively restrained．Research resuhs indicate that wavelet transform method is very useful for noise reduction in signals．Its precision is higher than that of the adaptive filtering method．)

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)

说明：  图像处理的位图操作，256色转为灰度图，图像处理入门源程序(Bitmap image processing operations, 256-color to grayscale, image processing, entry-source)