Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the var...
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ISBN:
(数字)9781510603349
ISBN:
(纸本)9781510603332;9781510603349
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the variation of the compression level of the studied image has been obtained. It is shown that the compression ratio in the range of 8-10 is optimal for environmental monitoring. Under these conditions the compression level is in the range of 1.7 - 4.2, depending on the type of images. It is shown that the algorithm used is more convenient and has more advantages than Winrar. The Haar wavelet algorithm has improved the method of signal and imageprocessing.
wavelet transform technique is applied to the analysis of data collected in experiments on the characterization of nonlinear optical materials which may be in the form of liquid, thin film or crystal. Many characteriz...
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ISBN:
(纸本)0819422134
wavelet transform technique is applied to the analysis of data collected in experiments on the characterization of nonlinear optical materials which may be in the form of liquid, thin film or crystal. Many characterization techniques are based on nonlinear optical processes such as higher harmonic generation in which second harmonic or third harmonic signals may be generated by the nonlinear material. When the optical path length of the material is changed, the interference between bound and free waves forms a fringe pattern. Conventional Fourier transform techniques are not suitable for analyzing such fringes when they have a variable periodicity and a low signal-to-noise ratio. However, the wavelet transform method is best suited for such signals because it provides a better resolution in both space and frequency domains. In this study, optical properties of materials are extracted from these fringe patterns by decomposing them into coefficients which are inner products of the signal and a family of wavelets generated from a mother wavelet by dilation and shift operations.
Efficient image watermarking techniques have been developed in the wavelet domain. Similar to other wavelet-based imageprocessing, the choice of wavelet filters generally affects the performance of a wavelet-based wa...
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Efficient image watermarking techniques have been developed in the wavelet domain. Similar to other wavelet-based imageprocessing, the choice of wavelet filters generally affects the performance of a wavelet-based watermarking system. In this paper, we evaluate the performance of a set of biorthogonal integer wavelets under a multiresolution-watermarking framework. Biorthogonal integer wavelets have been extensively used for imageapplications because they possess the linear-phase property and can be efficiently implemented. We find that the widely adopted 9/7-F wavelet achieves the best robustness performance. Further investigation is conducted to show that the superiority of the 9/7-F wavelet is primarily owing to its being nearly orthogonal.
The discrete wavelet transform was introduced as a linear operator. It works on signals that are modeled as functions from the integers into the real or complex numbers. Since many signals have finite function values,...
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ISBN:
(纸本)0819441929
The discrete wavelet transform was introduced as a linear operator. It works on signals that are modeled as functions from the integers into the real or complex numbers. Since many signals have finite function values, a linear discrete wavelet transform over a finite ring has been proposed recently. Another recent development is the research of nonlinear wavelet transforms triggered by the introduction of Sweldens' lifting scheme. This paper builds on these developments and defines an essentially nonlinear translation invariant discrete wavelet transform that works on signals that are functions from the integers into any finite set. As only discrete arithmetic is needed, such transforms can be calculated very time efficiently. The basic properties of these generalized discrete wavelet transforms are given along with explicit examples.
Dual-tree wavelet transforms have recently gained popularity [1] since they provide low-redundancy directional analyses of images. In our recent work, dyadic real dual-tree decompositions have been extended to the M-b...
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ISBN:
(纸本)1424407281
Dual-tree wavelet transforms have recently gained popularity [1] since they provide low-redundancy directional analyses of images. In our recent work, dyadic real dual-tree decompositions have been extended to the M-band case, so adding much flexibility to this analysis tool. In this work, we propose to further extend this framework on two fronts by considering (i) biorthogonal and (ii) complex M-band dual-tree decompositions. Denoising results are finally provided to demonstrate the validity of the proposed design rules.
We introduce a general framework for computing the continuous wavelet transform (CWT). Included in this framework is an FFT implementation as well as fast algorithms which achieve O(1) complexity per wavelet coefficie...
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ISBN:
(纸本)0819422134
We introduce a general framework for computing the continuous wavelet transform (CWT). Included in this framework is an FFT implementation as well as fast algorithms which achieve O(1) complexity per wavelet coefficient. The general approach that we present allows a straight forward comparison among a large variety of implementations. In our framework, computation of the CWT is viewed as convolving the input signal with wavelet templates that are the oblique projection of the ideal wavelets into one subspace orthogonal to a second subspace. We present this idea and discuss and compare particular implementations.
We present examples of a new type of wavelet basis functions that are orthogonal across shifts, but not across scales. The analysis functions are low order splines while the synthesis functions are polynomial splines ...
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ISBN:
(纸本)0819422134
We present examples of a new type of wavelet basis functions that are orthogonal across shifts, but not across scales. The analysis functions are low order splines while the synthesis functions are polynomial splines of higher degree n2. The approximation power of these representations is essentially as good as that of the corresponding Battle- Lemarie orthogonal wavelet transform, with the difference that the present wavelet synthesis filters have a much faster decay. This last property, together with the fact that these transformation s are almost orthogonal, may be useful for image coding and data compression.
In this paper, we link concepts from nonuniform sampling, smoothness function spaces, interpolation, and wavelet denoising to derive a new multiscale interpolation algorithm for piecewise smooth signals. We formulate ...
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ISBN:
(纸本)0819450804
In this paper, we link concepts from nonuniform sampling, smoothness function spaces, interpolation, and wavelet denoising to derive a new multiscale interpolation algorithm for piecewise smooth signals. We formulate the optimization of finding the signal that balances agreement with the given samples against a wavelet-domain regularization. For signals in the Besov space B-p(alpha)(L-p), p greater than or equal to 1, the optimization corresponds to convex programming in the wavelet domain. The algorithm simultaneously achieves signal interpolation and wavelet denoising, which makes it particularly suitable for noisy sample data, unlike classical approaches such as bandlimited and spline interpolation.
The problem we are interested in is the restoration of nuclear medicine images acquired by a gamma camera. In a previous paper(1) the authors have developed a wavelet, based filtering method enabling to remove one of ...
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ISBN:
(纸本)0819432997
The problem we are interested in is the restoration of nuclear medicine images acquired by a gamma camera. In a previous paper(1) the authors have developed a wavelet, based filtering method enabling to remove one of the major sources of error in nuclear medicine, namely Poisson noise. The purpose of this paper is to show how the restoration algorithm has been improved by introducing the point spread function as additional constraint in the restoration of the wavelet coefficients and choosing the regularization constraint in the object space. We describe a new restoration algorithm where filtering and deconvolution are coupled in a multiresolution frame. The performances are illustrated with simulated data and phantom images.
Blocking artifacts are the most objectionable drawback of block-based image and video coders. We describe a novel technique for removing blocking artifacts via multiscale edge processing. The new technique exploits th...
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ISBN:
(纸本)0819422134
Blocking artifacts are the most objectionable drawback of block-based image and video coders. We describe a novel technique for removing blocking artifacts via multiscale edge processing. The new technique exploits the advantages of an invertible multiscale edge representation from which the block edges can be easily identified and removed. By virtue of the multiscale edge processing one is able to deblock images effectively without blurring perceptually important features or introducing new artifacts. We present the deblocking algorithm with experimental results and a discussion.
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