In our paper we present innovative approach to objective quality evaluation that could be computed using mean difference between original and tested image in different wavelet subbands. DWT subband decomposition prope...
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ISBN:
(纸本)9780819474988
In our paper we present innovative approach to objective quality evaluation that could be computed using mean difference between original and tested image in different wavelet subbands. DWT subband decomposition properties are similar to human visual system (HVS) characteristics facilitating integration of DWT into image quality evaluation. DWT decomposition is done with multiresolution analysis of a signal that allows us to decompose a signal into approximation and detail subbands. DWT coefficients were computed using reverse biorthogonal spline wavelet filter banks. Coefficients for HH subband in level 2 are used to compute new image quality measure (IQM). IQM is defined as difference between HH level 2 coefficients of original and degraded image.
We present new quantitative results for the characterization of the L-2-error of wavelet-like expansions as a function of the scale a. This yields an extension as well as a simplification of the asymptotic error formu...
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ISBN:
(纸本)0819429139
We present new quantitative results for the characterization of the L-2-error of wavelet-like expansions as a function of the scale a. This yields an extension as well as a simplification of the asymptotic error formulas that have been published previously. We use our bound determinations to compare the approximation power of various families of wavelet transforms. We present explicit formulas for the leading asymptotic constant for both splines and Daubechies wavelets. For a specified approximation error, this allows us to predict the sampling rate reduction that can obtained by using splines instead Daubechies wavelets. In particular, we prove that the gain in sampling density (splines vs. Daubechies) converges to pi as the order goes to infinity.
The primary goal of this paper is to give examples of the recently developed (finite-field) wavelet coding method by studying the encoder and decoder for some half-rate codes. We propose a decoding methodology based o...
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ISBN:
(纸本)0780370414
The primary goal of this paper is to give examples of the recently developed (finite-field) wavelet coding method by studying the encoder and decoder for some half-rate codes. We propose a decoding methodology based on estimating the polyphase components of the channel error pattern. To demonstrate the striking computational savings of the wavelet coding method over alternatives, we show that bounded-distance decoding of the (24,12,8) Golay code requires only weight computations (or at the worst case, it needs a cyclic lookup table of table size 12). The simplicity and computational savings that finite field wavelets offer for the encoding and decoding of wavelet block codes indicate their powerful capacities for error control coding applications.
Conventional implementation of multi-dimensional wavelet transform (e.g. 3-D wavelet) requires whether a high amount of "in access" memory or a continual access to slow memory of a processor which makes it i...
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ISBN:
(纸本)0780376633
Conventional implementation of multi-dimensional wavelet transform (e.g. 3-D wavelet) requires whether a high amount of "in access" memory or a continual access to slow memory of a processor which makes it infeasible for most applications. In this paper, we proposed a novel algorithm for computation of an n-D discrete wavelet transform (DWT) based on lifting scheme. In addition to benefits of lifting scheme (which causes a major reduction in computational complexity and performs the total computations in time domain), our real-time approach computes the coefficients for all kinds of 1(st) and 2(nd) generation wavelets with short delay and optimized utilization of the slow and fast memories of a processor.
The application of wavelet transform can improve discrimination capability and signal-to-noise ratio of the correlation outputs with respect to the classical one. The concept of the associative storage in a photorefra...
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ISBN:
(纸本)0819429139
The application of wavelet transform can improve discrimination capability and signal-to-noise ratio of the correlation outputs with respect to the classical one. The concept of the associative storage in a photorefractive material offers suitable methods to design multichannel correlators for fingerprint identification. An optical system that employs holographic recording in a F-e: LiNbO3 crystal is proposed and experimentally demonstrated for the physical implementation of multichannel wavelet matched correlator. The scale of wavelet filter is optimized according to the robustness to the noise and discriminability of the filter. The photorefractive correlator is used as a ROM in the recognition. When the object beam with an input fingerprint is used for recovering, a set of correlation outputs are obtained in parallel along the directions of the reference beams, and detected by a CCD camera. Experimental results are promising for further use in the practice.
In this paper, a robust image hashing framework is proposed using image normalization, discrete wavelet transform and singular value decomposition. The stressed motive of the proposed scheme is to obtain a randomize h...
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ISBN:
(纸本)9781509055593
In this paper, a robust image hashing framework is proposed using image normalization, discrete wavelet transform and singular value decomposition. The stressed motive of the proposed scheme is to obtain a randomize hash sequence which can be used for image authentication and database search. For this purpose, the image is first normalized followed by hash generation in the wavelet domain utilizing the properties of singular value decomposition (SVD). Experimental evaluations demonstrate that the proposed scheme is providing the better robustness and security.
We explore the filtering properties of wavelets functions in order to develop accurate and efficient numerical algorithms for image Restoration problems. We propose a parallel implementation for MIMD distributed memor...
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ISBN:
(纸本)0819429139
We explore the filtering properties of wavelets functions in order to develop accurate and efficient numerical algorithms for image Restoration problems. We propose a parallel implementation for MIMD distributed memory environments. The key insight of our approach is the use of distributed versions of Level 3 Basic Linear Algebra Subprograms as computational building blocks and the use of Basic Linear Algebra Communication Subprograms las communication building blocks for advanced architecture computers. The use of these low-level mathematical software libraries garantees the development of efficient, portable and scalable high-level algorithms and hides many details of the parallelism from the user's point of view. Numerical experiments on a simulated image restoration applications are shown. The parallel software has been tested on a 12 nodes IBM SP2 available at the Center for Research on Parallel Computing and Supercomputers in Naples (Italy).
wavelet transforms have proven to be useful tools for several applications, including signal analysis, signal compression and numerical analysis. This paper surveys the VLSI architectures that have been proposed for c...
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wavelet transforms have proven to be useful tools for several applications, including signal analysis, signal compression and numerical analysis. This paper surveys the VLSI architectures that have been proposed for computing the Discrete and Continuous wavelet Transforms for I-D and 2-D signals. The architectures are based upon on-line versions of the wavelet transform algorithms. These architectures support single chip implementations and are optimal with respect to both area and time under the word-serial model.
Noise reduction has been a traditional problem in imageprocessing. Recent wavelet thresholding based denoising methods proved promising, since they are capable of suppressing noise while maintaining the high frequenc...
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ISBN:
(纸本)0780370414
Noise reduction has been a traditional problem in imageprocessing. Recent wavelet thresholding based denoising methods proved promising, since they are capable of suppressing noise while maintaining the high frequency signal details. However, the local space-scale information of the image is not adaptively considered by standard wavelet thresholding methods. In this paper, a new type of thresholding neural networks (TNN) is presented with a new class of smooth nonlinear thresholding functions being the activation function. Unlike the standard soft-thresholding function, these new nonlinear thresholding functions are infinitely differentiable. Then a new nonlinear 2-D space-scale adaptive filtering method based on the wavelet TNN is presented for noise reduction in images. The numerical results indicate that the new method outperforms the Wiener filter and the standard wavelet thresholding denoising method in both peak-signal-to-noise-ratio (PSNR) and visual effect.
We present a definition of wavelet-bicoherence based on wavelet-polyspectra. We propose a simple estimator for wavelet-bicoherence, and discuss its statistical properties. In particular it is shown that wavelet-bicohe...
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ISBN:
(纸本)0780370414
We present a definition of wavelet-bicoherence based on wavelet-polyspectra. We propose a simple estimator for wavelet-bicoherence, and discuss its statistical properties. In particular it is shown that wavelet-bicoherence estimates has a larger number of effective degrees of freedom than traditional Fourier-based bicoherence estimates. The proposed estimator is applied to detection of coherent couplings in rocket measurements from the ionospheric E-region. It is concluded that wavelet-bicoherence is a well suited toot for analysis of non-stationary mode coupling.
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