dwb_fusion

利用小波变换实现和直方图均衡化相对比的图像的增强与分割.应该比较有用.分割也采取了几种技术的对比(using wavelet transform and histogram equalization relative ratio of image enhancement and segmentation. Be more useful. Pm cutting has taken several technical contrast)

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)

基于gabor小波变换的论文，对做人脸识别很有用(Gabor wavelet transform-based papers, do face recognition is useful)

小波域图像滤波，采用双变量收缩函数发实现(Bivariate Shrinkage Functions for Wavelet-Based Denoising)

说明：  提出了一种基于复解析小波变换的相位诊断齿轮故障的方法。复解析小波变换将Hilbert变换与小波分析紧密结合在一起,具有自适应分析能力。利用复解析小波变换得到齿轮振动信号的相位,其功率谱图上可提取调制边频带结构来识别故障模式。试验结果表明这种方法可有效应用于齿轮局部故障诊断中。(A new method using the phase based on complex analytical wavelet transform for fault diagnosis of gears was proposed. The phase of vibration signals of gears is got by complex analytical wavelet transform, which combines Hilbert transform with wavelet transform tightly and possesses adaptive analysis ability. By making spectrum analysis of the phase, the sideband structure in power spectrum can be protruded, and the fault pattern can be identified. Experimental results show that the proposed method is effective in local defect detection of gears.)

小波变换实现微弱信号检测 BPSK QAM FSK(Wavelet transform weak signal detection BPSK QAM FSK)

说明：  近年来，随着互联网的高速发展，网上的多媒体信息也急剧增加，这些多媒体信息以图像为主。如何从浩瀚的图像数据库中快速、准确地找出所需要的图像，己成为一个备受关注的研究课题。有效地组织、管理和检索大规模的图像数据成为迫切需要解决的问题。于是基于内容的图像检索(Content-Based Image Retrieval: CBIR)作为一个崭新的研究领域出现了。 本课题拟研究、分析彩色图像红、绿、蓝三基色直方图的生成、特征提取和相似度等问题，应用图像的颜色信息—三基色直方图对图像进行检索。针对基于颜色的图像检索，本文采用应用广泛的RGB颜色空间来表示图像的颜色特征，对颜色分量进行等间隔量化并形成特征矢量并对特征矢量进行归一化处理，采用图像均匀分块的方法引入图像中色彩所处的位置信息，用距离度量函数进行图像的相似性匹配。在此基础上实现了基于三基色直方图算法的检索系统。 本文的研究和实践对于促进基于内容的图像数据库检索技术的应用具有一定的参考价值和实践意义。 (With the rapid development of Internet, the multimedia information is booming. All this information is mostly images. Effective recognizing, management and searching all these images have been an emergent problem. This has led the rise of a new research and development field: Content-Based Image Retrieval (CBIR). The topics to research, analysis color images red, green and blue color histogram generation, feature extraction and the similarity of the issues, application of the color image- trichromatic histogram of the image retrieval. Based on the color against the static image retrieval, this paper application of a wide range of RGB color space to indicate the color image features, the color components, such as spacing and quantitative characteristics of a feature vector and a normalization of vector processing, using uniform image block the introduction of the method in which the color image Location information, and distance measuring function similar to the image of the match. On)

图像处理中的小波变换C++源代码，含有使用文档和例子，非常全面！(image processing wavelet transform C source code, documentation and with the use of examples, very comprehensive!)

计算小波时间熵的源程序，内容详尽，调试正确，非常有用。计算小波时间熵的源程序，内容详尽，调试正确，非常有用。(Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful. Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful.)

小波方法进行降噪，阈值函数来完成不同设计，核心程序如下面的所示，使用的小波基有coif5，db3，sym4，bior2.4，haar，rbio(Wavelet method for noise reduction, design to complete different threshold function, the core program as shown below, using the wavelet base coif5, db3, sym4, bior2.4, haar, rbio )