In this paper we show that if wavelet domain processing is used with digital restoration, then pixel-scale features can be restored exactly in the absence of noise. In the presence of noise results are similar, except...
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ISBN:
(纸本)0819425915
In this paper we show that if wavelet domain processing is used with digital restoration, then pixel-scale features can be restored exactly in the absence of noise. In the presence of noise results are similar, except for some noise-amplification and ringing artifacts. wavelet domain modeling eliminates the need to discretize the image acquisition kernel and helps formulate image restoration as a discrete least squares problem. The performance of this technique is analyzed by model-based simulation using a comprehensive model to account for system blur at the image formation level, for the potentially important effects of aliasing, and for additive noise.
wavelet transforms computed by the decimated Mallat's algorithm present pyramidal aspect. This pyramidal analysis combined with a prediction of high-frequency coefficients is used to produce a magnified signal. Th...
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ISBN:
(纸本)0780362985
wavelet transforms computed by the decimated Mallat's algorithm present pyramidal aspect. This pyramidal analysis combined with a prediction of high-frequency coefficients is used to produce a magnified signal. The prediction is based on a zero-crossings representation and on the construction of a multiscale edge-signature database. Performances are evaluated for synthetic-noisy and natural images. A improvement regarding some classical methods is observed.
In this paper we propose a method of applying median filter in the wavelet domain in image segmentation when the image consisting of regions hard to be segmented by spatial domain median filter. The method transforms ...
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ISBN:
(纸本)0780374886
In this paper we propose a method of applying median filter in the wavelet domain in image segmentation when the image consisting of regions hard to be segmented by spatial domain median filter. The method transforms an image into the wavelet domain and then iteratively applies median filter in the wavelet domain and finally transforms result into the spatial domain. The advantage of wavelet domain median filter is that in the wavelet domain, probabilities of encountering root images are spread over sub-band images and therefore median filter is unlikely to encounter root images at early stage of iterations and can generate better result as iteration increases. Better performance are obtained in segmenting images having a Gaussian noise patter, especially when regions are close to each other in their mean values. Results from computer simulation are used to demonstrate superiority of the method.
We present a viewpoint of studying biorthogonal wavelets by using wavelet operators. A characterization of MRA biorthogonal wavelets is given in the framework of wavelet operators. An efficient wavelet filtering algor...
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ISBN:
(纸本)0819425915
We present a viewpoint of studying biorthogonal wavelets by using wavelet operators. A characterization of MRA biorthogonal wavelets is given in the framework of wavelet operators. An efficient wavelet filtering algorithm based on this characterization is applied to X-ray computerized tomography (CT) for multiresolution reconstruction and reduced X-ray exposure. Simulation results indicate that wavelet based reconstruction allows satisfactory image quality in a region of interest from local wavelet and global scaling components of projection data. The results are directly applicable to medical X-ray CT.
image coding using multirate filter banks and wavelets is evaluated in this paper. The coding systems considered are based on the M-channel general lapped biorthogonal transform (GLBT) and the embedded zerotree wavele...
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ISBN:
(纸本)0780374029
image coding using multirate filter banks and wavelets is evaluated in this paper. The coding systems considered are based on the M-channel general lapped biorthogonal transform (GLBT) and the embedded zerotree wavelet (EZW) coding methods, as well as the baseline JPEG standard. The study concentrates on both coding efficiency and complexity. The tradeoff between efficiency and complexity of each coding system has been analyzed. The coding results show that the choice of a coding scheme depends mainly on the applications at hand.
In this paper, we propose to use secret, key-dependent parametric wavelet filters to improve the security of digital watermarking schemes operating in the wavelet transform domain We show that the parametrization of w...
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ISBN:
(纸本)0780367251
In this paper, we propose to use secret, key-dependent parametric wavelet filters to improve the security of digital watermarking schemes operating in the wavelet transform domain We show that the parametrization of wavelet filters can be easily integrated into existing wavelet-based watermarking algorithms, resulting in improved security without additional computational complexity. Both, robustness and imperceptibility are adequate for many applications.
We present wavelet based video compression algorithms. The motion estimation and compensation, which is an essential part in the compression, is based on segment movements. The proposed based codec sequentially employ...
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ISBN:
(纸本)0780370414
We present wavelet based video compression algorithms. The motion estimation and compensation, which is an essential part in the compression, is based on segment movements. The proposed based codec sequentially employs the following steps: We first divide each frame in the sequence into blocks resulted from the block matching algorithm. The, we appply Hough transform, in order to group it into segments the blocks that have similar motion parameters. We estimate the motion parameters for each segment using several motion models and least-squares algorithm and apply motion compensation upon the frames in each group. In the wavelet domain an optimal vector bit allocation is being used to distribute the bit budget among consecutive frames. The manipulated frames in each group are quantized and coded using techniques from still image compression. The residual error of the compression is reduced by applying error correction in the wavelet domain to enhance the quality of the reconstructed sequence.
This paper introduces a new approach to color image denoising that exploits scale-specific, cross-component edge correspondences inherent in color image data. processing takes place in the wavelet Transform Modulus Ma...
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ISBN:
(纸本)0780362985
This paper introduces a new approach to color image denoising that exploits scale-specific, cross-component edge correspondences inherent in color image data. processing takes place in the wavelet Transform Modulus Maxima domain wherein image data is represented in terms of a set of multiscale edgemaps. Denoising is accomplished by building noise suppression masks which discriminate noise related edges from physically significant edges. Experimental results show that the new approach outperforms wavelet thresholding in images containing irregular textures.
If G is an orthonormal system in IL2 then for any function g is an element of G the function g(2) is a probability density. In this paper we discuss the properties of wavelet based densities and corresponding random v...
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ISBN:
(纸本)0819425915
If G is an orthonormal system in IL2 then for any function g is an element of G the function g(2) is a probability density. In this paper we discuss the properties of wavelet based densities and corresponding random variables.
Most of the noise models encountered in signalprocessing are either additive or multiplicative. However, the widely held wavelet shrinkage estimators for signal denoising deal only with additive noise. We propose a B...
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ISBN:
(纸本)0780376226
Most of the noise models encountered in signalprocessing are either additive or multiplicative. However, the widely held wavelet shrinkage estimators for signal denoising deal only with additive noise. We propose a Bayesian wavelet shrinkage model that encompasses both types of noise as well as noise that may exist between these two extremes. In applications such as SAR imaging, where multiplicative noise is predominant, statistical models intended for additive noise removal can effect a fair amount of restoration. This leads us to believe that noise in the signal can be considered as somewhere between multiplicative and additive. The new estimator removes noise by better adapting to the noise on hand. This approach is motivated by the, work of Pericchi [I] on the analysis of Box & Cox [2] transformations in the linear model. In addition, mixture priors governing the transformation are shown to be useful in predicting the noise from a choice of models. Experimental results are also reported.
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