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小波分解在图像放大缩小中的应用-wavelet decomposition in Image Zooming Application
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在采用二维离散小波变换对织物图像进行分解的基础上，引入了熵的概念，将小波熵作为织物图像的特征值，把熵值看作系统紊乱程度的度量，由此得到织物图像的小波熵特征值，通过与正常织物经过二维小波变换后提取的小波熵值相比较，熵值大者即认为有疵点存在-At the use of two-dimensional discrete wavelet transform decomposition of the fabric image, based on the introduction of the concep
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对采集到的电压信号进行小波包分解提取特征向量，再进行BP神经网络训练-On the acquisition of the voltage signal to the wavelet packet decomposition to extract feature vector and then BP neural network training
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針對傳統小波變換過程復雜的缺點和SPIHT算法編碼過程重復運算、存儲量大的問題,首先分析了小波基和小波分解層數的選擇,然后提出了一種新的可變閾值的SPIHT算法,該算法利用可變閾值對SPIHT算法中不重要像素列表(LIP)和不重要系數列表(LIS)進行分類得到一種更有效的編碼算法.仿真結果表明,該算法的壓縮整體性能要好于SPIHT算法.-Wavelet transform for the traditional complex process shortcomings and repeat th
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小波分解，能够对离散信号进行小波分解处理并重构-Wavelet decomposition, can be a discrete wavelet decomposition of signal processing and reconstruction
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Owing to the broad application value of audio
watermarking in remote transmission and mobile
extraction, it is very important to study watermarking
approaches against A/D and D/A conversion. Based
on wavelet decomposition and cepstrum technol
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Owing to the broad application value of audio
watermarking in remote transmission and mobile
extraction, it is very important to study watermarking
approaches against A/D and D/A conversion. Based
on wavelet decomposition and cepstrum technol
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Owing to the broad application value of audio
watermarking in remote transmission and mobile
extraction, it is very important to study watermarking
approaches against A/D and D/A conversion. Based
on wavelet decomposition and cepstrum technol
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BBB基于小波分解、互信息测度以及混合优化的图像配准-BBB based on wavelet decomposition, mutual information measure and the hybrid optimization of image registration
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文中的方法是把图像分块，小波分解得到低频分量、高频分量，然后计算每一块的对比度，把图像块划分为清晰块、模糊块，把清晰块和模糊块相邻的区域定义为边界区域，融合时，直接选取清晰块作为融合后的相应块，对于边界区域，在小波分解的基础上采用基于对比度的像素选取的方法进行处理。-Paper, the method is to image segmentation, wavelet decomposition are low frequency, high frequency components, then
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文章涉及了小波一维小波分解和重构的MATLAB程序，程序相当有借鉴意义。-Articles related to the wavelet one-dimensional wavelet decomposition and reconstruction of MATLAB program, the program quite a reference.
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基于多尺度小波分解的图像融合方法是目前最热门的方法之一。本文重点对基于小
波分解的图像配准和图像融合技术进行研究-Multi-scale wavelet decomposition based image fusion method is one of the most
popular methods. This thesis studies the image registration and image fusion technology
based on wavelet dec
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基于平移不变小波变换的多普勒速度声纳输出信号处理.针对水下航行器组合导航系统所使用的多普勒速度声纳输出信号的特点,采用了平移不变小波变换的多分辨率分析的方法,利用Daubechies小波函数,采用了半软阈值去噪的方法,能够在低信噪比的情况下准确地估计多普勒声纳的频移,从含有噪声的多普勒输出信号中提取出原始信号.通过仿真实验表明:采用4层小波分解,算法计算量减小,有效地消除多普勒噪声,从而提高水下组合导航系统的精度. -Doppler speed the sonar output signal p
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对信号进行两层提升分解，构造小波分解结构，使用函数wnoise获取噪声方差，接着使用函数wbmpen获取小波去噪阈值，最后使用函数实现信号去噪。-Signal two layers enhance decomposition, the constructed wavelet decomposition structure, function wnoise for noise variance, and finally use the function signal denoising.
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此文档主要是小波分解与重构的VC语言代码，可以直接运行，只要将信号输入。比较清晰的展现了小波分解与重构过程-This document is the the VC language code wavelet decomposition and reconstruction, and can be run directly, as long as the signal input. Comparison clearly shows the wavelet decomposition and rec
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应用db5小波和 bior4.4小波, 对图象cameraman.tif分别进行2层小波分解和重构-The application db5 wavelet bior4.4 of wavelet image cameraman.tif 2-layer wavelet decomposition and reconstruction
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信号的小波分解与重构原理，在matlab运行，内容详细，并有代码。-Principles of Signal based on wavelet decomposition and reconstruction, to run matlab, detailed, and code.
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小波分解被应用在众多领域，这篇文档是从网上摘录的资料，可帮助初学者利用matlab快速试难小波分解的用法和特点-Usage and characteristics of the wavelet decomposition be applied in many fields, this document is an excerpt from the online information that can help beginners quickly try hard wavelet decompo
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The code is for denoising using wavelet decomposition and reconstruction。 This is the implementation of paper "Efficient Image Denoising Method Based on a New Adaptive wavelet packet thresholding function"
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This paper describes a method for detecting faults
in the tap selector by means of vibration measurements during tap
changer operation, using envelope analysis based on Hilbert transform
and wavelet decomposition. Different failures at the tap
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