huidushuxingceliang

说明：  用optisystem制作得FBG 滤波器(FBG filter was made with optisystem)

根据论文Harris C. A combined corner and edge detector[J]. Proc Alvey Vision Conf, 1988, 1988(3):147-151实现Harris角点检测(Harris corner detection)

1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,p)/norm(W(:,p)) 8、若W不收敛，返回第5步 9、令p=p+1，若p小于等于m,返回第4步 剩下的应该都能看懂了 基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)

数字图像处理中的几何变换，包括图像的平移，图像的镜像，图像转置，图像的缩放，图像的旋转以及三种插值算法(The geometric transformation in digital image processing includes image translation, image mirroring, image transposition, image scaling, image rotation, and three interpolation algorithms)

数字图像处理第三版(冈萨雷斯)附带课件PPT，第七章，英文原版(Digital Image Processing PPT by Gonzalez & Woods(3rd edition)，Chapter 7)

对图像变形的一些基本算法的介绍和功能的描述等 (about marphing )

本程序实现小波和小波包滤波，，对高频部分进行处理对一维信号进行处理，得到重构去噪后的信号，代码调试通过(This procedure realize wavelet and wavelet packet filtering, and the high frequency part of the process of one dimensional signal processing, reconstruction after denoising signal, code debugging through)

基于matlab的图像小波融合测试程序，选取四副位图文件为对比(Matlab wavelet-based image fusion test program)

：近距离目标超高分辨率微波成像技术在安全检测、非破坏性控制、生物医学等领域中有着非常重要的应用 价值和广阔的应用前景。该文利用基于窄脉冲形式的超宽带时域雷达系统研究近距离目标的高分辨率ISAR成像， 给出了仿真和实测结果。利用转台旋转目标，基于超宽带脉冲源和超宽带收发天线以及高性能取样示波器，配以同 步触发脉冲和自行研发的数据采集软件，搭建了该时域雷达实验系统，提出了准确获取目标回波信息的实验条件， 和实现回波延时精确校正的误差补偿方法。并针对采样时间窗内的杂波干扰，讨论了时域后向投影算法(Back Projection，BP)与背景对消技术相结合的成像算法，实现了分辨率为 8 mm 的近距离目标的成像，准确地反映了 目标的位置、形状和大小等信息。( The high resolution imaging of near field targets are interesting for security, non-destructive control and biomedical application. In this paper, high resolution near field ISAR imaging is implemented using Ultra Wide Band (UWB) time domain radar system. Simulation and experiment are both conducted. The target is rotated by turntable. The system is built based on the UWB pulse source, UWB antennas, high performance sampling oscillograph, synchronous trigger pulse and proper motion study data acquisition software. Experiment condition and delay errors compensation method are presented to obtain accurate echo information of the target. And Back Projection (BP) combined with background cancel algorithm is discussed considering the clutter interference in time window. )

基于Visual C++的图像边缘检测工程，以Canny为例(Visual C++-based image edge detection works to Canny Case)