chedaoxian

一种自适应chirplet分解的快速算法 针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。 (Chirplet an adaptive decomposition algorithm for rapid adaptive signal decomposition Chirplet many unknown parameters, is more difficult to achieve the characteristics of the literature [1] proposed a new fast algorithm Chirplet decomposition. The algorithm calculating the signal function of the second phase, its energy distribution to be concentrated in the signal modulation frequency curve on the conclusions, this time through the spectral peak detection can be obtained simultaneously Chirplet tune the frequency, timing and magnitude of the estimated center then through the solution line technology of FM frequency and the width of the initial estimates, the simulation results verify the effectiveness of the algorithm.)

说明：  国外编写的双树复小波的一个开发包，包括1维和2维的情况，文件中有说明。(The Dual-Tree Complex Wavelet prepared outside of a development package, including the one-dimensional and two-dimensional case, the document has made it clear.)

dwt数字水印算法源代码，对剪切，加躁，旋转，JPEG压缩有较好的鲁棒性(dwt digital watermarking algorithm source code to shear, plus a bit, rotation, JPEG compression with better robustness)

2基于NSCT的遥感图像融合性能评价及分析.pdf(2 based on remote sensing image fusion performance evaluation and analysis of NSCT. PDF)

边缘检测法和阈值分割法，是图像分割技术应用中两项重要的方法。本文介绍了图像边缘检测和阈值分割的一般原理、典型算法以及研究现状。本文针对边缘检测算子和几种阈值分割技术进行了详细讨论。针对火柴根数统计和钢筋根数统计两个实验，在详细分析检测原理的基础上，编写了相应的实验并给出了实验结果。(Edge detection and thresholding method, image segmentation is an important technology in two ways. This article describes the general principles of image edge detection and thresholding, the typical algorithms and research status. In this paper, several edge detection operator and thresholding techniques are discussed in detail. Statistics for the number of matches and reinforced the number two experimental statistics, based on a detailed analysis of the detection principle, write the corresponding experimental and experimental results are given.)

该代码用于在视觉智能监控/视频监控/视觉监控/视频智能监控中，消除阴影。阴影消除对视频监控具有重要的意义，能够有效地降低阴影对目标检测的影响，减小误检率和漏检率，提高对目标的识别效率以及监控系统的稳定性和可靠性。(This code is used to remove shadow in visual intelligent surveillance/video surveillance/visual surveillance/video intelligent surveillance. Shadow removal plays a important role in video surveillance. It reduce the affection of shadow in object detection, decrease false detection rate and missing rate, and improve the stability and reliability of surveillance system.)

说明：  Hu矩定位图像，可以提取图像的特征，然后进行匹配定位(Hu Moment positioning images, can be extracted image features, and then proceed to match the positioning)

利用opencv+VC++实现对图像的边缘处理，从而对图像进行检测(Use opencv+ VC++ to achieve the edge of the image processing to the image detector)

lda线性特征提取，用于人脸识别，首先进行小波特征提取后用lda提取特征。(lda linear feature extraction for face recognition, first of all, after feature extraction using wavelet feature extraction using lda.)

视频图像处理，采用背景减除法中混合高斯建模进行视频前景和背景的分离(Video image processing, background subtraction method using Gaussian mixture modeling to separate the foreground and background video)