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.
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.
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.
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.
We give many examples of bivariate nonseparable compactly supported orthonormal wavelets which are supported over [0,3]x[0,3]. The Holder continuity properties of these wavelets are studied.
ISBN:
(纸本)0819425915
We give many examples of bivariate nonseparable compactly supported orthonormal wavelets which are supported over [0,3]x[0,3]. The Holder continuity properties of these wavelets are studied.
We discover a new relationship between two seemingly different image modeling methodologies;the Besov space theory and the wavelet-domain statistical image models. Besov spaces characterize the set of real-world image...
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ISBN:
(纸本)0819432997
We discover a new relationship between two seemingly different image modeling methodologies;the Besov space theory and the wavelet-domain statistical image models. Besov spaces characterize the set of real-world images through a deterministic characterization of the image smoothness, while statistical image models capture the probabilistic properties of images. By establishing a relationship between the Besov norm and the normalized likelihood function under an independent wavelet domain generalized Gaussian model, we obtain a new interpretation of the Besov norm which provides a natural generalization of the theory for practical imageprocessing. Based on this new interpretation of the Besov space, we propose a new image denoising algorithm based on projections onto the convex sets defined in the Besov space: After pointing out the limitations of Besov spaces, we propose possible generalizations using more accurate image models.
In this paper, we present a new method of image coding using two popular imaging tools, Zernike moments and wavelets. The main idea is that we can produce appropriate image descriptors by involving an appropriate numb...
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ISBN:
(纸本)0780375033
In this paper, we present a new method of image coding using two popular imaging tools, Zernike moments and wavelets. The main idea is that we can produce appropriate image descriptors by involving an appropriate number of moments, compressed in a form suitable to represent an image with low reconstruction error for pattern recognition applications. At this point the concept of wavelet compression is involved, which has already been discussed in many technical papers. We use an existent wavelet based compression algorithm, to compress not the 2-D image, but the resulted moment based 1-D signal. So, using this formulation we can achieve a compressed representation of the image, suitable for pattern recognition purposes and image retrieval tasks. It is very important to notice here the ability of Zernike moments to provide a very high level of image reconstruction, using the inverse wavelet transform, establishing a useful method.
In this work, we introduce a nonlinear geometric transform, called peak transform, for efficient image representation and coding. Coupled with wavelet transform and subband decomposition, the peak transform is able to...
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ISBN:
(纸本)9781424414369
In this work, we introduce a nonlinear geometric transform, called peak transform, for efficient image representation and coding. Coupled with wavelet transform and subband decomposition, the peak transform is able to significantly reduce signal energy in high-frequency subbands and achieve a significant transform coding gain. This has important applications in efficient data representation and compression. Based on peak transform (PT), we design an image encoder, called PT encoder, for efficient image compression. Our extensive experimental results demonstrate that, in wavelet-based subband decomposition, the signal energy in high-frequency subbands can be reduced by up to 60% if a peak transform is applied. The PT image encoder outperforms state-of-the-art JPEG2000 and H.264 (INTRA) encoders by up to 2-3 dB in PSNR (peak signal-to-noise ratio), especially for images with a significant amount of high-frequency components.
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