Factorization of orthogonal block circulant matrices can not be generalized in a straightforward way for block circulant matrices which are merely invertible. However, they can be decomposed into an orthogonal matrix ...
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ISBN:
(纸本)0819416274;9780819416278
Factorization of orthogonal block circulant matrices can not be generalized in a straightforward way for block circulant matrices which are merely invertible. However, they can be decomposed into an orthogonal matrix and an atom that represents the `nonorthogonal' part of the matrix. Atoms can be characterized by nilpotent block-companion matrices. This characterization permits, for example, to derive bounds for the width of the band of the inverse of a banded block circulant matrix.
This article presents two modelling methods using wavelet networks. Both methods are intended to be used for an acoustic pulse signal classifier. We present a few results obtained with signals coming from a recording ...
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ISBN:
(纸本)0818679204
This article presents two modelling methods using wavelet networks. Both methods are intended to be used for an acoustic pulse signal classifier. We present a few results obtained with signals coming from a recording of the percussive response of metal parts. The object of this application is the non-destructive testing of these parts, as defects perturb the acoustic signature. The first modelling method uses wavelet networks to perform a non-linear regression on the signal to be classified. The second consists of non-linear auto-recursive modelling of the signal by means of the networks. The use of wavelet networks enables us to combine the generalizing capacities of neural networks with the efficiency of wavelet analysis of pulse signals.
In this paper, we propose a new algorithm for extracting a non smooth shape from its noisy observation. The key ideal is to project the noisy shape onto a set of orthogonal subspaces at different resolutions, and cons...
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ISBN:
(纸本)0819432997
In this paper, we propose a new algorithm for extracting a non smooth shape from its noisy observation. The key ideal is to project the noisy shape onto a set of orthogonal subspaces at different resolutions, and construct scale space representation gleaned from the locally smoothed shape. Using the curvature we proceed to filter the high resolution scale subspace by projecting it onto the scale which is in turn used for the reconstruction. Inspired by the conjugate mirror filter and the wavelet decomposition synergy, we propose a curvature based filter operating at different scales and with minimal knowledge about the noise statistics.
On the base of local criteria of processing quality, a class of local adaptive linear filters for image restoration and enhancement is introduced. The filters work in a running window in the domain of DFT of DCT and h...
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ISBN:
(纸本)0819422134
On the base of local criteria of processing quality, a class of local adaptive linear filters for image restoration and enhancement is introduced. The filters work in a running window in the domain of DFT of DCT and have O (size of the window) computational complexity thanks to recursive algorithms of running DFT and DCT. The filter design and the recursive computation of running DCT are outlined and filtering for edge preserved noise suppression, blind image restoration and enhancement is demonstrated.
Density conditions have turned out to be a powerful tool for deriving necessary conditions for weighted wavelet systems to possess an upper or lower frame bound. In this paper we study different definitions of density...
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ISBN:
(纸本)0819450804
Density conditions have turned out to be a powerful tool for deriving necessary conditions for weighted wavelet systems to possess an upper or lower frame bound. In this paper we study different definitions of density and compare them with respect to their appropriateness and practicality.
This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable fre...
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ISBN:
(纸本)0780362985
This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable free parameters, which are constructed based on an integer version of Haar transform. Our learning method is to determine such free parameters using some subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet transform has the feature of the subimages. We apply such a wavelet transform to high frequency components of a reference image and check whether they are vanished of not, to detect a target subimage.
We present a packetization method for robust image transmission over packet erasure channels. The packets are formed in such a way that the image information is spread over different frequency bands and spatial locati...
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ISBN:
(纸本)0780370414
We present a packetization method for robust image transmission over packet erasure channels. The packets are formed in such a way that the image information is spread over different frequency bands and spatial locations to avoid complete disruption of certain image blocks in case of a packet loss. Experimental results are provided to demonstrate the performance of this method.
Textured image is considered as the repetition of some primitives with a certain rule of displacement, thus every region in the image has different periodic structure. The segmentation is realized by its self-imaging ...
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ISBN:
(纸本)0819416274
Textured image is considered as the repetition of some primitives with a certain rule of displacement, thus every region in the image has different periodic structure. The segmentation is realized by its self-imaging effect. A series of Fresnel images can be obtained at the fractional Talbot distances depended on the periodicity of the original. All these images are a summation of the Fourier frequency modulated by a phase factor, which related with the fractional Talbot distance. Therefore, these images can be considered as the multichannel Talbot transform of the original image and represent the texture features to a certain extent. By comparing these images, different texture regions are segregated. Theoretical analysis and primitive experimental results are presented.
Dyadic wavelet transform has been used to derive affine invariant functions. The invariant functions are based on the dyadic wavelet transform of the object boundary. Two invariant functions have been calculated using...
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ISBN:
(纸本)0819437646
Dyadic wavelet transform has been used to derive affine invariant functions. The invariant functions are based on the dyadic wavelet transform of the object boundary. Two invariant functions have been calculated using different numbers of dyadic levels. Experimental results show that these invariant functions outperform some traditional invariant functions. The stability of these invariant functions have been tested for a large perspective transformation.
Multiresolution signal and image models such as the hidden Markov tree (HMT) aim to capture the statistical structures of smooth and singular (textured and edgy) regions. Unfortunately, models based on the orthogonal ...
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ISBN:
(纸本)0780362985
Multiresolution signal and image models such as the hidden Markov tree (HMT) aim to capture the statistical structures of smooth and singular (textured and edgy) regions. Unfortunately, models based on the orthogonal wavelet transform suffer from shift-variance, making them less accurate and realistic. In this paper, we extend the HMT modeling framework to the complex wavelet transform, which features near shift-invariance and improved angular resolution compared to the standard wavelet transform. The model is computationally efficient (featuring linear-time computation and processing algorithms) and applicable to general Bayesian inference problems as a prior density for the data. We develop a simple multiscale maximum likelihood classification scheme based on the complex wavelet HMT that outperforms methods based on real-valued wavelet HMTs. The resulting classifier can be used as a front end in a more sophisticated multiscale segmentation algorithm.
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