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ch09_JPEG2000
- 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
wavelet_dec
- 用于多分辨率分解，使用 A trous 算法； 在分解的过程中，同时给出各级的细节和概貌，它们和原数据有着同样的长度。-for multiresolution decomposition, use A trous algorithm; The decomposition process, and given levels of detail and picture, and the original data is the same length.
wavelet_rec
- 用于多分辨率分析中的重建，使用 A trous 算法-for multiresolution analysis of the reconstruction algorithm used A trous
EEG_ana
- 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
Contourlet
- Contourlet变换的实现源码。相关理论可参考:Do M N, Vetterli M. \"The contourlet transform: an efficient directional multiresolution image representation\" [J]. Image Processing, IEEE Transactions on, 2005, 14 (12): 2091-2106.
A wavelet based multiresolution algorithm for rota
- 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
foveate
- creates foveated image based on Gaussian multiresolution pyramid. Uses formula from Geisler and Perry (1998) to determine spatial dropoff around a point of gaze-creates foveated image based on Gaussian multiresolution pyramid. Uses formula from Geis
MODWT-c.zip
- 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
Atoolbox
- 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.
Multiresolutionwavelettransformdecompositionandrec
- 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
Chapter07
- wavelets and multiresolution processing
cupbook
- 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
tuxiangpipei
- 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
gauss_wavelet
- ，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
LENGQIANG
- 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
study-on-multiresolution
- 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
contourlet_txform
- Contourlet小波经典文献:The Contourlet Transform: An Efficient Directional Multiresolution Image Representation-The Contourlet Transform: An Efficient Directional Multiresolution Image Representation
jnd-using-wavelets
- In this paper, we propose a new perceptual model for balanced multiwavelet (BMW) transforms. The latter transform achieves simultaneous orthogonality and symmetry without requiring any input prefiltering. The proposed model is derived using m
An-improved-Hilbert-Huang-method-for-analysis-of-
- 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
Wavelets
- 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