General stereo image matching provides an adequate but hard problem with sufficient complexity, with which the potential of wavelets may be exploited to a full extend. An ideal stereo image matching algorithm is suppo...
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ISBN:
(纸本)0819422134
General stereo image matching provides an adequate but hard problem with sufficient complexity, with which the potential of wavelets may be exploited to a full extend. An ideal stereo image matching algorithm is supposed to be invariant to the scale, translation, rotation, and partial correspondence between two given stereo images. While the multi-resolution of wavelets is good at scale adaptivity, we also require the wavelet transform and pyramids to be translation- and rotation-invariant. this paper is intended to serve for three purposes: (1) To present the general problem of stereo image matching in a sufficient depth and extent, so that pure wavelet mathematicians could think on adequate and efficient solutions, (2) To present a complete algorithm for top-down image matching including surface reconstruction by using wavelet pyramids, (3) To search for a wavelet family optimal for image matching. It is expected that a family of adequately designed wavelets could provide a generic and robust solution to the stereo image matching problem, which could be an important breakthrough in computer vision, photogrammetry, and pattern recognition.
this paper describes different methodologies for noise reduction or denoising withapplications in the field of microscopy. An in depth study on wavelet- and polynomial based denoising has been performed by considerin...
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ISBN:
(纸本)0819422134
this paper describes different methodologies for noise reduction or denoising withapplications in the field of microscopy. An in depth study on wavelet- and polynomial based denoising has been performed by considering standard test images and phantom tests with moderate and high levels of Gaussian noise. Different thresholding methods have been tested and evaluated and in particular a novel sigmoidal- type thresholding method has been proposed. In real applications, noise variance estimation problem becomes crucial because most of the thresholding estimators tends to overestimate this value. A comparison withthe Hermite polynomial transform (HPT) and a modification of the HPT based in detecting the position and orientation of relevant edges has been accomplished. From this study one can conclude that bothwavelet-based and polynomial-based denoising methods perform better than any other nonlinear filtering method both in terms of perceptual quality and edge-preserving characteristics.
Analysis of surface profile generally involves filtering to separate short wavelengths from medium and long wavelengths. this is usually accomplished using digital filters. the wavelet filter is an ideal means to sepa...
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ISBN:
(纸本)0819422134
Analysis of surface profile generally involves filtering to separate short wavelengths from medium and long wavelengths. this is usually accomplished using digital filters. the wavelet filter is an ideal means to separate the profile into different bands. the space frequency localization and multiscale presentation of different wavelength components is useful in manufacturing process control and in establishing relationship between surface texture and function. the use of wavelet filter to analyze surface is explored in this paper. this paper deals withthe evaluation of suitable wavelet basis for analyzing surface texture of machined surfaces using wavelet filter. the multiscale surface features are analyzed using wavelet filter to explore the potential use of wavelet filter in monitoring of manufacturing process and feature detection in engineering surfaces.
the extraction of character image is an important front-end processing for optical character recognition (OCR) and other applications. this process is extremely important because the OCR applications usually extract s...
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ISBN:
(纸本)0819422134
the extraction of character image is an important front-end processing for optical character recognition (OCR) and other applications. this process is extremely important because the OCR applications usually extract salient features and process on them. the existence of noise not only destroys features of characters, but also introduces unwanted features. We propose a new algorithm which removes unwanted background noises from a textual image. Our algorithm is based on the observation that the magnitude of the intensity variation of character boundaries differs form that of noises at various scales of their wavelet transform. therefore, most of the edges corresponding to the character boundaries at each scale can be extracted using a thresholding method. the internal region of characters is determined by a voting procedure, which uses the arguments of the remaining edges. the interior of recovered characters is solid containing no holes. Characters tend to become fattened, because of the smoothness being applied in the calculation of wavelet transform. To obtain a quality restoration of character image, the precise locations of characters at the original image are then estimated using a Bayesian criterion. Detailed algorithm with careful analysis of the free parameters are also conducted in this paper. the method is simple and effective. We also present some experimental results that suggest its effectiveness.
A viable approach to noise filtering in a spatially heterogeneous environment consists of considering a multiresolution representation of the noisy image, nd of applying a different adaptive filter to each layer. the ...
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A discrete scaled Gabor representation (SRG) is developed to meet the requirements of localized and refined time- frequency representation of signals. SGR generalizes the metaplectic structure by using windows' tr...
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ISBN:
(纸本)0819422134
A discrete scaled Gabor representation (SRG) is developed to meet the requirements of localized and refined time- frequency representation of signals. SGR generalizes the metaplectic structure by using windows' translation, modulation and dilation as synthesis waveforms. Fundamental features and importance of SGRs are discussed. We derive fast algorithms for the computation of related analysis sequences at different scales. An example of using SGRs for refined time-frequency representation is also demonstrated. A significant feature of SGRs also lies in the fact that they can be realized in a parallel FFT-based implementation structure.
Atmospheric blocking during three unusual winter months is studied by multiresolution analysis and a wavelet based adaptation of traditional Fourier series based energetics. We demonstrate that blocking, in part a lar...
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ISBN:
(纸本)0819422134
Atmospheric blocking during three unusual winter months is studied by multiresolution analysis and a wavelet based adaptation of traditional Fourier series based energetics. We demonstrate that blocking, in part a large and localized meteorological phenomenon, is largely described by just the largest scale part of the multiresolution analysis. New forms of the transfer functions of kinetic energy withthe mean and eddy parts of the atmospheric circulation are introduced. these quantify the spatially localized conversion of energy between scales. A new accounting method for wavelet indexed transfers permits the introduction of a physically meaningful localized scale flux function. these techniques are applied to the data, and some support is found for the hypothesis that blocking is partially maintained by an inverse cascade.
this paper is concerned withthe problem of determining performance of a wavelet-based hybrid neurosystem trained to provide efficient feature extraction and signal classification. the hybrid network consists of a par...
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ISBN:
(纸本)0819422134
this paper is concerned withthe problem of determining performance of a wavelet-based hybrid neurosystem trained to provide efficient feature extraction and signal classification. the hybrid network consists of a parallel array of neurosystems. Each neurosystem is constructed withthree single neural networks; two of which are feature extraction networks, and the other is a classification network, are provided with magnitude and location information of the wavelet transform coefficients, respectively, and are trained with self-organizing rules. their outputs are then presented to the classification network for pattern recognition. Based on the topological maps provided by the feature extraction neural networks, the back-propagation algorithm is used to train the third network for pattern recognition. the combination of wavelet, wavelet transform, and hybrid neural network architecture and advanced training algorithms in the design makes the system unique and provides high classification accuracy. In this paper, system performance is shown to be intrinsically related to basis kernel function used in feature extraction. A method for selecting the optimal basis function and a performance analysis using simulated data under various noise condition are presented and compared against other pattern recognition techniques.
In this work, we present a new family of image compression algorithms derived from Shapiro's embedded zerotree wavelet (EZW) coder. these new algorithms introduce robustness to transmission errors into the bit str...
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A large number of terrain images were taken at Aberdeen Proving Grounds, some containing ground vehicles. Is it possible to screen the images for possible targets in a short amount of time using the fractal dimension ...
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ISBN:
(纸本)0819422134
A large number of terrain images were taken at Aberdeen Proving Grounds, some containing ground vehicles. Is it possible to screen the images for possible targets in a short amount of time using the fractal dimension to detect texture variations. the fractal dimension is determined using the wavelet transform for these visual images. the vehicles are positioned within the grass and in different locations. Since it has been established that natural terrain exhibits a statistical l/f self-similarity property and the psychophysical perception of roughness can be quantified by the same self-similarity, fractal dimensions estimates should vary only at texture boundaries and breaks in the tree and grass patterns. Breaks in the patterns are found using contour plots of the dimension estimates and are considered as perceptual texture variations. Variation in the dimension estimate is considered more important than the accuracy of the actual dimensions number. Accurate variation estimates are found even with low resolution images.
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