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EWT20130617

于 2016-07-30 发布 文件大小:1343KB
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代码说明：

  由加州理工大学教授开发的经验小波变换算法程序包，经检验比小波效果更好(California Institute of Technology developed by Professor experiences wavelet transform algorithm package, the test better than wavelet effect)

文件列表：

EWT20130617
...........\EWT
...........\...\1D
...........\...\..\disp_hhs2.m,2100,2016-07-20
...........\...\..\EWT1D.m,2202,2016-07-20
...........\...\..\EWT_beta.m,162,2016-07-20
...........\...\..\EWT_Meyer_FilterBank.m,1474,2016-07-20
...........\...\..\EWT_Meyer_Scaling.m,920,2016-07-20
...........\...\..\EWT_Meyer_Wavelet.m,1325,2016-07-20
...........\...\..\Hilbert_EWT.m,1313,2016-07-20
...........\...\..\iEWT1D.m,841,2016-07-20
...........\...\..\Modes_EWT1D.m,708,2016-07-20
...........\...\..\Show_EWT.m,1142,2016-07-20
...........\...\..\Show_EWT_Boundaries.m,977,2016-07-20
...........\...\2D
...........\...\..\Curvelet
...........\...\..\........\AnglesLocalMax.m,1442,2016-07-20
...........\...\..\........\AnglesLocalMaxMin.m,2182,2016-07-20
...........\...\..\........\Angular_sector.m,9804,2016-07-20
...........\...\..\........\CreateAngleGrid.m,1270,2016-07-20
...........\...\..\........\EWT2D_Curvelet.m,4892,2016-07-20
...........\...\..\........\EWT2D_Curvelet_FilterBank.m,8118,2016-07-20
...........\...\..\........\EWT2D_Curvelet_Scaling.m,971,2016-07-20
...........\...\..\........\EWT_Angles_Detect.m,3819,2016-07-20
...........\...\..\........\iEWT2D_Curvelet.m,856,2016-07-20
...........\...\..\........\ShowCurveletFilters.m,736,2016-07-20
...........\...\..\........\Show_Curvelets_boundaries.m,4532,2016-07-20
...........\...\..\........\Show_EWT2D_Curvelet.m,713,2016-07-20
...........\...\..\drawArcEllipse.m,338,2016-07-20
...........\...\..\drawCircle.m,179,2016-07-20
...........\...\..\drawEllipse.m,182,2016-07-20
...........\...\..\Littlewood-Paley
...........\...\..\................\EWT2D_LittlewoodPaley.m,2323,2016-07-20
...........\...\..\................\EWT2D_Meyer_FilterBank.m,1529,2016-07-20
...........\...\..\................\EWT2D_Meyer_Scaling.m,1011,2016-07-20
...........\...\..\................\EWT2D_Meyer_Wavelet.m,1410,2016-07-20
...........\...\..\................\EWT2D_UP_Meyer_Wavelet.m,1175,2016-07-20
...........\...\..\................\iEWT2D_LittlewoodPaley.m,1144,2016-07-20
...........\...\..\................\LP_boundaries.m,788,2016-07-20
...........\...\..\Ridgelet
...........\...\..\........\EWT2D_Ridgelet.m,2339,2016-07-20
...........\...\..\........\iEWT2D_Ridgelet.m,1006,2016-07-20
...........\...\..\Show_EWT2D_Filters.m,583,2016-07-20
...........\...\..\Tensor
...........\...\..\......\EWT2D_Tensor.m,2955,2016-07-20
...........\...\..\......\iEWT2D_Tensor.m,1467,2016-07-20
...........\...\..\......\Show_EWT2D_Tensor.m,853,2016-07-20
...........\...\..\......\Tensor_Plot_Boundaries.m,1354,2016-07-20
...........\...\Boundaries
...........\...\..........\binomialtail.m~,121,2016-07-20
...........\...\..........\EWT_Boundaries_Completion.m,835,2016-07-20
...........\...\..........\EWT_Boundaries_Detect.m,4436,2016-07-20
...........\...\..........\FTC
...........\...\..........\...\FTC_Histogram_Segmentation.m,1093,2016-07-20
...........\...\..........\...\ftc_seg.c,16026,2016-07-20
...........\...\..........\LocalMaxima
...........\...\..........\...........\LocalMax.m,1223,2016-07-20
...........\...\..........\...........\LocalMaxMin.m,1458,2016-07-20
...........\...\..........\MorphoMath
...........\...\..........\..........\FunctionClosing.m,646,2016-07-20
...........\...\..........\..........\FunctionDilation.m,766,2016-07-20
...........\...\..........\..........\FunctionErosion.m,762,2016-07-20
...........\...\..........\..........\FunctionGranulometry.m,590,2016-07-20
...........\...\..........\..........\FunctionOpening.m,646,2016-07-20
...........\...\..........\..........\FunctionTopHat.m,625,2016-07-20
...........\...\..........\NFABinomial.m~,232,2016-07-20
...........\...\..........\PowerLaw
...........\...\..........\........\Powerlaw_Estimator.m,712,2016-07-20
...........\...\README.txt,3616,2016-07-20
...........\...\README.txt~,3574,2016-07-20
...........\...\Tests
...........\...\.....\1D
...........\...\.....\..\Disp_HHT.m,244,2016-07-20
...........\...\.....\..\lfm.mat,15472,2016-07-20
...........\...\.....\..\seismic.mat,52273,2016-07-20
...........\...\.....\..\sig1.mat,33972,2016-07-20
...........\...\.....\..\sig2.mat,49617,2016-07-20
...........\...\.....\..\sig3.mat,47849,2016-07-20
...........\...\.....\..\sig4.mat,110288,2016-07-20
...........\...\.....\..\Test_EWT1D.m,3222,2016-07-20
...........\...\.....\..\Test_FTCBoundaries.m,1959,2016-07-20
...........\...\.....\..\texture.mat,360725,2016-07-20
...........\...\.....\2D
...........\...\.....\..\barb.mat,235601,2016-07-20
...........\...\.....\..\lena.mat,56440,2016-07-20
...........\...\.....\..\Save_EWT2D_Curvelet.m,956,2016-07-20
...........\...\.....\..\Save_EWT2D_LP.m,984,2016-07-20
...........\...\.....\..\Save_EWT2D_Tensor.m,1062,2016-07-20
...........\...\.....\..\Test_EWT2D_Curvelet.m,2119,2016-07-20
...........\...\.....\..\Test_EWT2D_LP.m,1632,2016-07-20
...........\...\.....\..\Test_EWT2D_Ridgelet.m,1617,2016-07-20
...........\...\.....\..\Test_EWT2D_Tensor.m,1677,2016-07-20
...........\...\.....\..\texture.mat,360725,2016-07-20
...........\license.txt,1313,2016-07-20

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  • xiaoboshang
    说明：  计算小波分解后的能量及小波熵。里面还有OFDM信号和WPM信号的程序。(After calculating the energy of wavelet decomposition and wavelet entropy. There is also OFDM signal and the WPM signal process.)
    2011-03-31 10:41:02下载
    积分：1
  • 20140521
    利用小波变换检测回波,经过labview显示，实现了很好的界面效果(Using wavelet transform to detect echoes through labview display interface to achieve a good effect)
    2014-05-21 09:36:26下载
    积分：1
  • lift97mlhard
    个人编写的提升格式97小波去噪，采用硬阈值法，三层分解，包括小波变换，去噪，逆变换三步(Written format of 97 individuals to enhance the wavelet denoising using hard threshold method, three decomposition, including wavelet transforms, denoising, inverse transform three-step)
    2020-06-29 04:20:02下载
    积分：1
  • thresold
    说明：  基于小波变换阈值去噪的MATLAB源代码（包含小波包去噪程序）(threshold based on wavelet transform Denoising MATLAB source code (including wavelet denoising packet procedure))
    2020-11-24 22:09:34下载
    积分：1
  • jubunengliang
    表面肌电信号的小波包局部能量分解柱状图，提取特征能量(Local energy of the surface EMG wavelet packet decomposition histogram feature extraction energy)
    2020-06-30 05:40:02下载
    积分：1
  • frit_toolbox_rar
    对图像进行脊波变换，包含实例，与小波变换的对比实例(Ridgelet image transformation, including examples of the contrast with the example of wavelet transform)
    2009-05-13 14:29:53下载
    积分：1
  • 40
    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)
    2009-10-21 11:37:34下载
    积分：1
  • Ship-detection
    复杂杂波背景下，海面红外图像中舰船目标检测的关键是如何降低虚警、检测出真正的 目标。为了实现这个目标，首先利用Haar小波函数进行小波变换，对图像进行预处理；然后进行恒 虚警检测（CFAR）；第三步采用行程法对检测的目标进行标记；最后采用管道滤波法剔出虚假目标， 检测出真正的目标。经仿真实验证明，此方法能有效地降低虚警，在复杂杂波背景中检测出目标。 (The key of ship detection in sea infrared image with complex clutter background is how to reduce false alarms and detect true targets.In order to achieve this aim,a novel algorithm is proposed. First,Haar wavelet transform technology is used as preprocessing,then constant false alarm rate(CFAR) detetion,then run-length label to mark objects detected by the above step,finally pipeline filter to reduce false alarms and detect true targets.Experiment results indicate that this method can effectively reduce false alarms and detect true targets in complicated sea background. )
    2012-03-12 14:14:55下载
    积分：1
  • DirFilter-test_pic
    简单的方向滤波器， 带测试图的， 可以直接运行(Simple directional filter, with a test chart, you can directly run)
    2012-09-11 19:46:21下载
    积分：1
  • rgbwavelet
    彩色RGB图像小波变换，并且重构出低频、中频、高频各个频带子块的图像。(RGB image wavelet and restruct the different frequency band)
    2021-04-11 16:08:58下载
    积分：1
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