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wavadapt
- 基于离散小波变换的自适应滤波算法分析与研究基于离散小波变换的自适应滤波算法分析与研究-DWT-based adaptive filtering algorithm analysis and research based on the discrete wavelet transform adaptive filtering algorithm analysis and research
Wavelet_based_full_scale_adaptive_digital_watermar
- 自适应全尺度小波数字图像水印.09年5月份 在清华学报出版的。实现大容量的水印嵌入，对于各种攻击的鲁棒性。请大家共享-Full-scale wavelet adaptive digital image watermarking .09 years in May, published in the Journal of Tsinghua University. The realization of large-capacity watermark embedding, the robustne
SNU-2
- Wavelets and JPEG2000: A brief review Beyond wavelets and JPEG2000 My exploration Directional wavelet construction Adaptive wavelet selection Inter-subband transform Outlook
24-05-09
- A New Robust Watermark Embedding into Wavelet DC Components
wavelet
- 基于小波系数块能量分析的自适应数字水印算法-Energy analysis based on wavelet coefficients of adaptive digital watermarking algorithm
WignerVille2014
- 本文将小波图像分解和信息熵特征提取相结合，提出一种新的掌纹特征提取算法。该算法首先对掌纹灰度图像进行二维小波分解，再利用多分辨信息熵分别计算不同尺度下的能谱熵作为特征向量，从而实现掌纹特征提取。该算法不但避免了图像增强和纹理细化等预处理过程，而且运用多分辨信息熵的自适应计算方法来调节分解级数，使得到的特征向量长度远小于传统算法。-In this paper, wavelet image decomposition and information entropy feature extractio
Marx20110509
- 本文将小波图像分解和信息熵特征提取相结合，提出一种新的掌纹特征提取算法。该算法首先对掌纹灰度图像进行二维小波分解，再利用多分辨信息熵分别计算不同尺度下的能谱熵作为特征向量，从而实现掌纹特征提取。该算法不但避免了图像增强和纹理细化等预处理过程，而且运用多分辨信息熵的自适应计算方法来调节分解级数，使得到的特征向量长度远小于传统算法。-In this paper, wavelet image decomposition and information entropy feature extractio
lossless-image-compression-based-on-optimal.pdf.z
- The optimal predictors of a lifting scheme in the general n-dimensional case are obtained and applied for the lossless compression of still images using rst quincunx sampling and then simple row-column sampling. In each case, the e ciency of the
N_sensors-12-13212-v2
- This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance
Matlab-Code-for-wavelet-denoising
- 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"
Adaptive-wavelet-threshold
- 小波变换自适应阈值，毕业设计可以参考关于阈值的选定，图像去噪，这是CNKI上的文献-Adaptive wavelet threshold
xiaobipcnn
- 图像融合论文，基于提升小波变换与自适应PCNN的医学图像融合方法-Image fusion papers, medical image fusion method based on lifting wavelet transform and adaptive PCNN' s
Recent-timefrequency-analysis
- Nonstationary signal analysis one of the main topics in the field of machinery fault diagnosis.Time-frequency analysis can identify the signal frequency components, reveals their time variant features,and is an effective tool to extract machinery h
A-Robust-Denoising-Algorithm
- In this paper, a robust DWPT based adaptive bock algorithm with modified threshold for denoising the sounds of musical instruments is proposed. The signal is first segmented into multiple blocks depending upon the minimum mean square criteria in each
10.1016@j.jvcir.2008.11.006.pdf
- this paper allows the shape adaptive wavelet to do region based image retri
kalman
- 利用了小波分析以及自适应性卡尔曼滤波降低了信噪比，非常实用的论文-Use of wavelet analysis and adaptive Kalman filter reduces the signal to noise ratio, very practical papers
pxc-methode
- Image enhancement is the indispensable features in image processing to increase the contrast of the remote sensing data and to provide better transform representation of the remote image data. This paper presents a new method to improve the
Adaptive--wavelet
- 本文讲述了地震面波压制，提高信噪比，剔除干扰信号-Adaptive attenuation of ground roll via continuous wavelet transform (1)
Wavelet-Shrinkage_-Asymptopia_
- 小波变换阈值去噪的文章，基于最大最小准则计算-Minimax Estimation, Adaptive Estimation, Nonparametric Regression, Density Estimation, Spatial Adaptation, Wavelet Orthonormal bases, BesovSpaces, Optimal Recovery.
Empirical-wavelet-transform
- 最近的一些方法，如经验模式分解 （EMD），提出将信号分解 其包含的信息。尽管它的适应性似乎 对于许多应用程序，这种方法的主要问题 是它缺乏理论。本文提出了一种新的方法 建立自适应小波。主要的想法是提取不同 设计适当的小波滤波器组的信号模式。 这种结构导致我们到一个新的小波变换，称为 经验小波变换。许多实验 显示此方法相比经典的有用性 EMD-Some recent methods, like the Empirical Mode Decompositio