We investigate three approaches to VLSI implementation of wavelet filters. The direct form structure, the lattice form structure, and an algebraic structure are used to derive different architectures for wavelet filte...
详细信息
ISBN:
(纸本)0819422134
We investigate three approaches to VLSI implementation of wavelet filters. The direct form structure, the lattice form structure, and an algebraic structure are used to derive different architectures for wavelet filters. The algebraic structure exploits conjugacy properties in number fields. All approaches are explained in detail for the Daubechies 4- tab filters. We outline the philosophy of a design method for integrated circuits.
Dyadic wavelet transform has been used to derive affine invariant functions. The invariant functions are based on the dyadic wavelet transform of the object boundary. Two invariant functions have been calculated using...
详细信息
ISBN:
(纸本)0819437646
Dyadic wavelet transform has been used to derive affine invariant functions. The invariant functions are based on the dyadic wavelet transform of the object boundary. Two invariant functions have been calculated using different numbers of dyadic levels. Experimental results show that these invariant functions outperform some traditional invariant functions. The stability of these invariant functions have been tested for a large perspective transformation.
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...
详细信息
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.
We show the relevance of multifractal analysis for some problems in image. This paper deals the characterization of brain tumor in magnetic resonance imaging. We introduce a declination of wavelet Leaders that recentl...
详细信息
ISBN:
(纸本)9781467325851;9781467325837
We show the relevance of multifractal analysis for some problems in image. This paper deals the characterization of brain tumor in magnetic resonance imaging. We introduce a declination of wavelet Leaders that recently been shown to provide practioners with a robust and efficient tool for the multifractal analysis of signals and images. We calculated new multiresolution parameters called average of wavelet coefficient and the log-cumulate derived from the wavelet leaders and we have solved the problem posed by the choice of interval regression that enters in the calculation of different parameters ( h(q), D(q), zeta(q)). We analyze and compare our estimator and simulated image against wavelet leaders. We apply the approach developed on different cerebral images in order to distinguish between different tissues corresponding to the healthy and pathological.
signalprocessing and imaging of biomedical phenomena pose significant challenges, with one dominant issue being that biological processes are usually time varying and non-stationary. Many traditional processing appro...
详细信息
signalprocessing and imaging of biomedical phenomena pose significant challenges, with one dominant issue being that biological processes are usually time varying and non-stationary. Many traditional processing approaches are derived on assumptions of statistical stationarity and linear time-invariant propagation channels, which are not valid assumptions for many biomedical problems. In this paper, continuous wavelet transforms are shown to be appropriate tools for characterizing linear time-varying systems and propagation channels and for processing wideband signals in non-stationary Gaussian noise. Wideband processing of signals allows for the processing to be limited by the scattering object's acceleration versus the more common techniques where the processing is limited by the scattering object's velocity. It is shown that the continuous wavelet transform of the output signal with respect to the input signal provides a correct system characterization for time-varying channels and non-stationary signals. Finally, an approach to removing even the wideband limitation of acceleration is presented. Possible biomedical applications of this approach include bloodflow velocimetry and heart motion monitoring.
The general area of signal and imageprocessing that focuses upon the detection and identification of military targets is known as automatic target recognition. This paper compares the impact of alternative wavelet pr...
详细信息
ISBN:
(纸本)0819424846
The general area of signal and imageprocessing that focuses upon the detection and identification of military targets is known as automatic target recognition. This paper compares the impact of alternative waveletprocessing techniques upon the performance of neural networks being used for target detection. In particular, the use of a filter whose coefficients are a linear combination of wavelet coefficients gave rise to an energy distribution in which targets were more detectable with fewer false alarms than when the same targets were sought in images whose data dimensionality was reduced using a conventional wavelet.
Volume data such as those acquired by magnetic resonance imaging techniques can be compressed efficiently using the wavelet transform. wavelet compression methods need to retain both the value and the location of the ...
详细信息
ISBN:
(纸本)0819422134
Volume data such as those acquired by magnetic resonance imaging techniques can be compressed efficiently using the wavelet transform. wavelet compression methods need to retain both the value and the location of the significant coefficients. We present experimental results demonstrating the use of zerotree encoding methods in wavelet compression can enhance the ability to further compress volume data.
Polarization in optical waveguides is always an aspect of optical loss and consequently impacts device performance. waveletimageprocessing allows a means to detect optical signals buried under noise. Orthogonality i...
详细信息
ISBN:
(纸本)0819445878
Polarization in optical waveguides is always an aspect of optical loss and consequently impacts device performance. waveletimageprocessing allows a means to detect optical signals buried under noise. Orthogonality is an essential element in wavelet bases. There are three primary types of multiresolution bases: orthogonal wavelet bases, semiorthogonal wavelet bases, and biorthogonal wavelet bases. waveletimageprocessing will be applied to laser beam propagation in lithium niobate and nonlinear polymer waveguides to achieve detection of signals below noise and a better understanding of polarization as an aspect of device performance.
In this paper speckle reduction is approached as a Wiener-like filtering performed in the wavelet domain by means of an adaptive shrinkage of the detail coefficients of an undecimated decomposition. The amplitude of e...
详细信息
ISBN:
(纸本)0819441929
In this paper speckle reduction is approached as a Wiener-like filtering performed in the wavelet domain by means of an adaptive shrinkage of the detail coefficients of an undecimated decomposition. The amplitude of each coefficient is divided by the variance ratio of the noisy coefficient to the noise-free one. All the above quantities are analytically calculated from the speckled image, the speckle variance, and the wavelet filters. On the test image Lenna corrupted by synthetic speckle, the proposed method outperforms Kuan's LLMMSE filtering by almost 3 dB SNR. Experiments carried out on true and synthetic speckled images demonstrate that the visual quality of the results is excellent in terms of both background smoothing and preservation of edge sharpness and textures. The absence of decimation in the wavelet decomposition avoids the typical ringing impairments produced by critically-subsampled wavelet-based denoising.
wavelet analysis and its application has found much attention in recent times. It is vastly applied in many applications such as involving transient signal analysis, imageprocessing, signalprocessing and data compre...
详细信息
ISBN:
(纸本)9780819489326
wavelet analysis and its application has found much attention in recent times. It is vastly applied in many applications such as involving transient signal analysis, imageprocessing, signalprocessing and data compression. It has gained popularity because of its multiresolution, subband coding and feature extraction features. The paper describes efficient application of wavelet analysis for image compression, exploring Daubechies wavelet as the basis function. wavelets have scaling properties. They are localized in time and frequency. wavelets separate the image into different scales on the basis of frequency content. The resulting compressed image can then be easily stored or transmitted saving crucial communication bandwidth. wavelet analysis because of its high quality compression is one of the feature blocks in the new JPEG2000 image compression standard. The paper proposes Daubechies wavelet analysis, quantization and Huffman encoding scheme which results in high compression and good quality reconstruction.
暂无评论