rendring2006

Images of diffraction

说明：  利用边界匹配算法恢复受损图像寻找最优运动矢量(edge detection function [hough_space,hough_circle,para] = hough_circle(BW,step_r,step_angle,r_min,r_max,p) )

按照夹角余弦距离计算待测样品与样品库的样品相似度(Cosine distance calculation in accordance with the test sample and the sample database sample similarity)

对场景分类和语义特征稀疏化的高层图像表示(Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification)

基于opencv实时图像的2值化处理，一定要有摄像头(Opencv-based real-time image processing of two values, there must be a camera)

粒子滤波算法实现目标定位的程序，matlab(Particle filter algorithm targeting program)

介绍了混合高斯背景建模法提取运动目标的过程，自己写的，比较好理解，付视频一个，用自己的视频也可以(Describes the process of Gaussian mixture background modeling method to extract moving target, write your own, is better understood, paid a video, you can use your own videos)

该文档是自适应信号处理研究的一篇研究生毕业论文，介绍了自适应的几种常见算法，如LMS，NLMS等等，并在最后有相关的MATLAB程序（LMS程序 自适应滤波器，陷波器，分离器等程序）可以作为自适应信号处理初学者的参考资料(This document is an adaptive signal processing graduate thesis introduces several common adaptive algorithms, such as LMS, NLMS, etc., and the final program has an associated MATLAB (LMS process adaptive filter, notch , splitters and other procedures) can be used as a reference adaptive signal processing information for beginners)

将原始载体图片经过一维冗余离散小波变换分成四个子频带，分别对每个子频带进行奇异值分解， 将水印图片灰度值直接按比例缩小嵌入到奇异值矩阵中，再将此矩阵进行一次奇异值分解得到奇异值当做此子带的奇异值， 重建此子带矩阵，而后将进行反冗余离散小波变换得到嵌入载体后的水印图像。(The original image after the one-dimensional vector redundant discrete wavelet transform is divided into four subbands, respectively, of each sub-band for the singular value decomposition, the watermark image gray value scale down directly embedded into the matrix singular value, then this matrix is ​ ​ a Singular value decomposition singular value as the singular values ​ ​ of this sub-band, the reconstruction of this sub-band matrix and after anti-redundant discrete wavelet transform watermark image after embedding the carrier.)

二进小波多级分解。基于二进小波的图像度尺度分解和边缘检测，效果还行。(into two multi-level wavelet decomposition. Based on Wavelet Image degrees scale decomposition and edge detection, the results were OK.)