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从子带编码到小波编码
子带编码
多分辨率分析
滤波器组与多分辨率
从子带编码到小波编码
小波分解图像方法
失真的度量方法
JPEG2000介绍-from subband coding to wavelet encoding subband coding multiresolution analysis filters with a resolution from the subband coding of wavelet image coding wavelet de
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二维图像的小波分解与重构，并画图显示。通过多分辨率分析实现。-2D image wavelet decomposition and reconstruction, and drawing show. Through multiresolution analysis to achieve.
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利用小波变换的EEG信号的多分辨率分析,利用小波变换的EEG信号的多分辨率分析-using wavelet transform EEG signal multiresolution analysis, The wavelet transform EEG signal multiresolution analysis
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dwt小波变换，用于对图像的处理与压缩-dwt wavelet transform, for the image processing and compression
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Maximal Overlap Discrete Wavelet Transformation, implemented in C.
Shift invariant transform, useful for application of multiresolution time series analysis. Includes basic Wavelet coefficients Haar, Daubechies, Least Asymmetric.,Maximal Overlap
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A collection of functions is presented which includes 2nd generation wavelet decomposition and reconstruction tools for images as well as functions for the computation of moment invariants. The wavelet schemes rely on the lifting scheme of Sweldens.
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HARR小波的VC实现源代码,能用于人脸检测与识别-HARR wavelet implementation of the VC source code, can be used for Human Face Detection and Recognition
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基于小波变换的图像的多分辨率方法以及重构的实现-Wavelet-Based Multiresolution decomposition and reconstruction of the achievement
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利用多分辨尺度小波进行图象纹理提取（两个参数，R1可以选择1.1-1.2，R2是阈值，可以选择10-30）-The use of multiresolution wavelet to extract texture images (two parameters, R1 can choose to 1.1-1.2, R2 is the threshold, you can choose to 10-30)
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Image Processing and Data Analysis - A multiscale approach
GOOD Ebook about image and data processing using Wavelet multiresolution analysis and other related technique-Image Processing and Data Analysis- A multiscale approach
GOOD Ebook ab
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基于小波变换的多分辨匹配算法:
首先利用小波的多分辩率特性将匹配图像和模板图像分解到乙层上，并且只保留LL低频部分，然后利用归一化相关法作为相似性度量，进行由粗到细的相关匹配过程，每次利用下一层的匹配结果在上层小范围内搜索。这样做极大地减少了搜索空间，而且减少了每次匹配计算相似度的数据量。
-Wavelet multiresolution matching algorithms: a wavelet multi-resolution feature will match the imag
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形状特征是武器装备目标识别的关键因素。针对归一化后轴夹角的特点和小波描述子多尺度描述轮廓曲
线的特性，提出一种R树索引的分层检索技术模型，在模型库空间逐级过滤出与目标相似的模板，以保证检索的效
率和准确性，并通过对军用车辆的检索实验验证了模型的有效性。-The shape features of military weapons＆equipment are the most important key factors of image
object recognition．Aimin
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，分析探讨了有关高斯函数的小波特性。根据多尺度微分算予理论和多分辨分析思
想，证明了高斯函数构造了一个多分辨分析(MRA)，高斯函数的各阶导数均构成小波基函数-Analysis of the characteristics of the Gaussian wavelet function. According to the theory of multi-scale differential operator and multi-resolution analysis thinking th
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面几章介绍了加细方程，多分辨分析（MRA）和离散小波变换（DWT）的基本思想，和基本函数的一些基本性质，如：逼近阶，矩量和点值。-Chapters describes the surface refinement equation, multiresolution analysis (MRA) and the discrete wavelet transform (DWT) of the basic idea, and some basic properties of the basic fun
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本文推导了二维矩形域上的正交多分辨分析与多尺度空间，构造了
相应的尺度函数和小波函数，以及它们的对偶函数，阐述了利用矩形域
上的双正交小波压缩分割图像的原理，并给出了计算步骤.
-This two-dimensional rectangular domain is derived orthogonal multiresolution analysis and multi-scale space, constructed the corresponding scaling functi
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Contourlets是由抽样的拉普拉斯金字塔(娜laeianPyramid，廿)滤波器和抽样的方向性滤波器组成的小波变换。兰州大学硕士论文，关于多分辨率分析的-Contourlets by sampling Laplacian pyramid (Na laeianPyramid, twenty) filter and sampling the composition of the directional wavelet transform filter. Master' s thesis
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The Hilbert–Huang method is presented with modifications,
for time-frequency analysis of distorted power quality signals.
The empirical mode decomposition (EMD) is enhanced with
masking signals based on fast Fourier transform (FFT), for separat
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该文提出了一种图像识别方法,该方法首先对识别图像进行多尺度小波分解, 把不同尺度的分解结果组织为分解向量, 再对分解向量作变换.-This paper presents a method of image recognition, the method based on recognition of image wavelet decomposition, the decomposition results of different scales for decomposition vector
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1 Haar Wavelets
1.1 The Haar transform
1.2 Conservation and compaction of energy
1.3 Haar wavelets
1.4 Multiresolution analysis
1.5 Compression of audio signals
1.6 Removing noise from audio signals
1.7 Notes and references
2 Daub ech
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Daubachies basis function for matlab wavelet multiresolution
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