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.
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.
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.
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.
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.
We present planar curve descriptors that allow a hierarchical representation of curves. The descriptors are based on wavelet and multiwavelet transforms and they decompose a curve into components of different scales.
ISBN:
(纸本)0819429139
We present planar curve descriptors that allow a hierarchical representation of curves. The descriptors are based on wavelet and multiwavelet transforms and they decompose a curve into components of different scales.
In this paper, the relationship between wavelet transform and Differential Mapping Singularities Theory (DMST) is discussed in the context of image compression. DMST maps 3-D surfaces accurately, with exact results, a...
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ISBN:
(纸本)0819425915
In this paper, the relationship between wavelet transform and Differential Mapping Singularities Theory (DMST) is discussed in the context of image compression. DMST maps 3-D surfaces accurately, with exact results, and to construct an image compression algorithm based on an expanded set of operations. This set includes shift, scaling rotation, and homogenous nonlinear transformations. This approach permits the mathematical description of a full set of singularities that describe edges and other specific points of objects. The edges and specific points (degenerate critical points) are the product of mapping smooth 3-D surfaces, which can be described by a simple set of polynomials that are suitable for image compression and Automatic Target Recognition (ATR). In signal and imageprocessing, wavelets have been used for several years to provide multi-resolution data representation [1] Originally, wavelets were developed for one-dimensional signal decomposition. Subsequently, they were generalized to 2-D image coding. Now, wavelet transform is used to hierarchically decompose an input signal into a series of lower resolution reference signals and associated detail signals. At each level, a reference signal and its associated detail signal contain information required to reconstruct the reference signal at the next higher resolution level. Efficient image coding is enabled by allocating the bandwidth according to the relative importance of information in the reference and detail signals, and then applying the next level of the lossy and lossless compression algorithm.
In this paper, we propose a method of efficient computation of wavelet coefficients from DCT-based coded image/video signals. Block transform domain filtering is well suited for transcoding of such data. First direct ...
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ISBN:
(纸本)0819422134
In this paper, we propose a method of efficient computation of wavelet coefficients from DCT-based coded image/video signals. Block transform domain filtering is well suited for transcoding of such data. First direct transform domain processing removes the necessary of inverse transform. Second, the number of nonzero elements in the blocks are significantly smaller than spatial domain. Therefore, the amount of computation can be reduced accordingly. Finally, the block processing algorithm provides a parallel processing method. Hence a fast implementation of the algorithm is well suited.
image watermarking is in use for proving ownership for a fairly long time. For most of the study on this area, a pseudo random number sequence PRSN or a binary image logo is embedded as watermark. Nowadays the owner...
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ISBN:
(纸本)9781467373869
image watermarking is in use for proving ownership for a fairly long time. For most of the study on this area, a pseudo random number sequence PRSN or a binary image logo is embedded as watermark. Nowadays the owner's face or sound is also embedded as biometric watermark. image is transferred to discrete wavelet transform domain, watermark is embedded to DWT values, then DWT values are retransformed to spatial domain to obtain watermarked image. Embedding a vector image logo as watermark was not tried in previous works. In this work, non-blind robust watermarking is applied using a vector image as watermark. Various attacks are applied to watermarked images and for each of these attacks vector image watermark is obtained equal or almost equal to the original. Embedding vector image as watermark will bring a new discipline for image watermarking and a new development will arise in this perspective.
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