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update-lifting
相关语句
  更新提升
     A new method for constructing the nonlinear update-lifting morphologic wavelet is presented.
     提出了一种新的构造非线性更新提升形态小波的方法.
短句来源
     The update-lifting wavelet the using generalized update operator is applied to image denoising. Experimental results show that the lifting morphologic wavelet has better denoising performance and less edge loss in detail image compared to the traditional wavelet thresholding method, expecially in a low signal to noise ratio.
     将采用了广义更新算子的更新提升小波应用于图像去噪,对比实现结果表明,与传统小波阈值去噪方法相比,该提升形态小波具有更好的去噪性能,细节图像中的边缘损失很小,尤其在低信噪比情况下性能更加优越.
短句来源
  “update-lifting”译为未确定词的双语例句
     PERFECT RECONSTRUCTION WITH ADAPTIVE UPDATE-LIFTING SCHEMES
     用自适应提升格式对信号精确重构(英文)
短句来源
  相似匹配句对
     EDA UPDATE
     EDA风景线
短句来源
     Component Update
     元器件快览
短句来源
     AL-31F Update
     AL-31F前景看好
短句来源
     BROWN-BROYDEN UPDATE ALGORITHM
     Brown-Broyden修正算法
短句来源
     Lifting sheaves
     提升的层结构
短句来源
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This paper treats several adaptive update\|lifting schemes for perfect reconstruction, which do not require bookkeeping in their calculations. In succession, we study their advantages and disadvantages more precisely. At last, we give a new method in choosing these adaptive update\|lifting filters, which is proved better than the method in .

本文分析了几种自适应提升格式在信号精确重构中的应用 ,在其计算过程中 ,它们均无须考虑当前步骤之前的数据。并分析了它们的优缺点。最后 ,提出一种构造自适应提升格式的方法 ,通过计算表明 ,此方法能取得更好的效果

A new method for constructing the nonlinear update-lifting morphologic wavelet is presented. The information of the detail signal is used to modify the scale signal, which also guarantees the perfect reconstruction feature of wavelet transform. The update operator of the update-lifting morphologic wavelet is extended. The generalized update operator is presented, which consists of a series of mathematical morphologic operators filtering the detail signals in spatial space. The update-lifting...

A new method for constructing the nonlinear update-lifting morphologic wavelet is presented. The information of the detail signal is used to modify the scale signal, which also guarantees the perfect reconstruction feature of wavelet transform. The update operator of the update-lifting morphologic wavelet is extended. The generalized update operator is presented, which consists of a series of mathematical morphologic operators filtering the detail signals in spatial space. The update-lifting wavelet the using generalized update operator is applied to image denoising. Experimental results show that the lifting morphologic wavelet has better denoising performance and less edge loss in detail image compared to the traditional wavelet thresholding method, expecially in a low signal to noise ratio.

提出了一种新的构造非线性更新提升形态小波的方法.它利用细节信号的信息改进尺度信号,并且可以保证该小波变换具有完备重构特性.对更新提升形态小波中的更新算子进行了拓展,提出了广义更新算子,它由一系列对细节信号空域滤波的数学形态学算子综合构成.将采用了广义更新算子的更新提升小波应用于图像去噪,对比实现结果表明,与传统小波阈值去噪方法相比,该提升形态小波具有更好的去噪性能,细节图像中的边缘损失很小,尤其在低信噪比情况下性能更加优越.

In this paper,a new method for 2D adaptive lifting wavelet transform is proposed,which suite for the task of image compression applications.It is based on a update lifting operator and a nonlinear prediction lifting operator according with certain local characteristic and statistical information of an image.Some experiment results show that the entropy of the coefficients in the transform domain obtained with this new method is smaller than that obtained with other adaptive wavelet transform method and non-adaptive...

In this paper,a new method for 2D adaptive lifting wavelet transform is proposed,which suite for the task of image compression applications.It is based on a update lifting operator and a nonlinear prediction lifting operator according with certain local characteristic and statistical information of an image.Some experiment results show that the entropy of the coefficients in the transform domain obtained with this new method is smaller than that obtained with other adaptive wavelet transform method and non-adaptive wavelet transform,which can avoid quantization with the image detail signals being zero(or almost zero)at the smooth gray-level variation areas at big probability.

基于图像的局部特性和统计信息,该文提出一种新的二维自适应提升小波变换方法。该方法通过构造基于图像局部特性的自适应更新算子和基于图像统计信息的非线性预测算子,对图像进行自适应的提升小波变换,与文献中的自适应小波变换方法和非自适应小波变换方法进行对比实验,该文方法所得到的高频子带的熵更低,含零高频系数更多,更有利于图像的压缩编码。

 
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