The aim of industrial process control is to convert measurements, taken while the process is evolving, into parameters which can be used to control the process. To be of practical use this must all be computationally ...
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ISBN:
(纸本)9780819464811
The aim of industrial process control is to convert measurements, taken while the process is evolving, into parameters which can be used to control the process. To be of practical use this must all be computationally efficient allowing real-time feedback. Electrical tomography measurements have the potential to provide useful data without intruding into the industrial process, but produce highly correlated and noisy data, and hence need sensitive analysis. The commonly used approaches, based on regularized image reconstruction are slow, and still require image post-processing to extract control parameters. An alternative approach is to directly work with the measurement data. We demonstrate an approach using wavelets to relate such electrical measurements to the state of flow within a pipe, and hence classify the state of the flow to one of a number of regimes. wavelets are an ideal tool for our purpose since their multi-scale nature enables the efficient description of both transient and long-term signals. The resulting wavelet models can be used to classify flow into one of a set of regimes, either for later study of the flow profile or for monitoring of an ongoing process. We illustrate our methods by application to simulated data sets.
Active infrared thermography is a non-destructive testing (NDT) technique used for non-contact inspection of components and materials by temporal mapping of thermal patterns by means of infrared imaging. Through the a...
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ISBN:
(纸本)9780819464811
Active infrared thermography is a non-destructive testing (NDT) technique used for non-contact inspection of components and materials by temporal mapping of thermal patterns by means of infrared imaging. Through the application of a short heat pulse, thermal waves of various amplitudes and frequencies are launched into the specimen allowing a signal analysis based on amplitude and phase information (pulsed phase thermography PPT). The wavelet transform (with complexwavelets) can be used with PPT data in a similar way as the classical Fourier transform however with the advantage of preserving time information of the signal which can then be correlated to defect depth, and in this way allowing a quantitative evaluation. In this paper we review the methodology of PPT and the associated signal analysis (Fourier analysis, wavelet analysis) to obtain quantitative defect depth information. We compare and discuss the results of thermal FEM simulations with experimental data and show the advantages of wavelet based signal analysis for defect depth measurements and material characterization.
Weighted medians over multichannel signals are not uniquely defined. Due to its simplicity, Astola et al.'s Vector Median (VM) has received considerable attention particularly in imageprocessingapplications. In ...
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Weighted medians over multichannel signals are not uniquely defined. Due to its simplicity, Astola et al.'s Vector Median (VM) has received considerable attention particularly in imageprocessingapplications. In this paper, we show that the VM and its direct extension the Weighted VM are limited as they do not fully utilize the cross-channel correlation. In fact, VM treats all sub-channel components independent of each other. By revisiting the principles of Maximum Likelihood estimation of location in a multivariate signal space, we propose two new and conceptually simple multichannel weighted median filters which can capture cross-channel information effectively. Their optimal filter derivations are also presented, followed by a series of simulations from color image denoising to array signalprocessing where the advantages of the new filtering structures are illustrated.
In magnetic resonance (MR) imaging, there is a tradeoff between the spatial resolution, temporal resolution and signal to noise ratio (SNR). MR images usually suffer from low SNR and low resolutions. In order to make ...
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ISBN:
(纸本)0819464236
In magnetic resonance (MR) imaging, there is a tradeoff between the spatial resolution, temporal resolution and signal to noise ratio (SNR). MR images usually suffer from low SNR and low resolutions. In order to make it practical for MR imaging with higher resolutions as well as sufficient SNR, it is necessary to reduce noise efficiently while preserving important image features. In this paper, we propose to use the wavelet-based multiscale level-set curve evolution algorithm to reduce noise for MR imaging. Experimental results demonstrate that this denoising algorithm can significantly improve the SNR and contrast to noise ratio (CNR) for MR images while preserving edges with good visual quality. The denoising results indicate that in MR imaging applications, we can almost doubly improve the temporal resolution or improve the spatial resolution while achieving sufficient SNR, CNR, and satisfactory image quality.
Optical properties of radially polarized light generated by liquid crystal (LC) polarization-converting devices with two LC molecular orientations (+/- 180 degrees and +/- 90 degrees twist modes) are measured and the ...
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Optical properties of radially polarized light generated by liquid crystal (LC) polarization-converting devices with two LC molecular orientations (+/- 180 degrees and +/- 90 degrees twist modes) are measured and the applicability to optical wavelet transforms (WTs) are discussed. It is found that the radially polarized lights in both the +/- 180 degrees and +/- 90 degrees twist modes can be regarded as wavelets. Based on the principle of WT, feature extractions of a simple binary image are carried out by applying the LC polarization-converting device to a shadow-casting system. Unique feature extraction properties of the shadow-casting system using the LC polarization-converting device and a LC microlens array are discussed. It is experimentally confirmed that edge and corner features are successfully extracted using the LC polarization-converting device with +/- 180 degrees and +/- 90 degrees twist modes, respectively. (c) 2006 Optical Society of America.
wavelets have been widely used in signal and imageprocessing for the past 20 years, In this paper,, we present an overview of the various methods of the wavelet transform in medical image fusion. Using wavelet transf...
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ISBN:
(纸本)081946080X
wavelets have been widely used in signal and imageprocessing for the past 20 years, In this paper,, we present an overview of the various methods of the wavelet transform in medical image fusion. Using wavelet transform, we presented a general image fusion scheme involves decomposition of the input images, calculation of the wavelet transform modulus. fusion strategy, and reconstruction for new fusion image. Next we provide a survey of recent wavelet developments in medical image fusion. In each case, we provide the reader with some general background information and a brief explanation of how the methods work.
Affine systems are reproducing systems of the form A(C)={DcTk psi(l):1 <= l <= L, k is an element of Z(n), c is an element of C} which arise by applying lattice translation operators T-k to one or more generator...
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Affine systems are reproducing systems of the form A(C)={DcTk psi(l):1 <= l <= L, k is an element of Z(n), c is an element of C} which arise by applying lattice translation operators T-k to one or more generators psi(l) in L-2(R-n), followed by the application of dilation operators D-c associated with a countable set C of invertible matrices. In the wavelet literature, C is usually taken to be the group consisting of all integer powers of a fixed expanding matrix. In this paper, we develop the properties of much more general systems, for which C = {c = ab: a is an element of A. b is an element of B} where A and B are not necessarily commuting matrix sets. C need not contain a single expanding matrix. Nonetheless, for many choices of A and B, there are wavelet systems with multiresolution properties very similar to those of classical dyadic wavelets. Typically, A expands or contracts only in certain directions, while B acts by volume-preserving maps in transverse directions. Then the resulting wavelets exhibit the geometric properties, e.g., directionality, elongated shapes, scales, oscillations, recently advocated by many authors for multidimensional signal and imageprocessingapplications. Our method is a systematic approach to the theory of affine-like systems yielding these and more general features. (c) 2005 Elsevier Inc. All rights reserved.
Registration is a fundamental step in imageprocessing systems where there is a need to match two or more images. applications include motion detection, target recognition, video processing, and medical imaging. Altho...
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Registration is a fundamental step in imageprocessing systems where there is a need to match two or more images. applications include motion detection, target recognition, video processing, and medical imaging. Although a vast number of publications have appeared on image registration, performance analysis is usually performed visually, and little attention has been given to statistical performance bounds. Such bounds can be useful in evaluating image registration techniques, determining parameter regions where accurate registration is possible, and choosing features to be used for the registration. In this paper, Cramer-Rao bounds on a wide variety of geometric deformation models, including translation, rotation, shearing, rigid, more general affine and nonlinear transformations, are derived. For some of the cases, closed-form expressions are given for the maximum-likelihood (ML) estimates, as well as their variances, as space permits. The bounds are also extended to unknown original objects. Numerical examples illustrating the analytical performance bounds are presented.
Object-based segmentation is the first essential step for imageprocessingapplications. Recently, satellite image segmentation techniques have been developed, but not enough to preserve the significant information co...
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Object-based segmentation is the first essential step for imageprocessingapplications. Recently, satellite image segmentation techniques have been developed, but not enough to preserve the significant information contained in the small regions of an image. The proposed method is to partition the image into homogeneous regions by using a fuzzy hit-or-miss operator with an inherent spatial transformation, which enables the preservation of the small regions. In the algorithm proposed here, an iterative segmentation technique is formulated as consequential processes. Then, each time in iterating, hypothesis testing is used to evaluate the quality of the segmented regions with a homogeneity index. The segmentation algorithm is unsupervised and employs few parameters, most of which can be calculated from the input data. This comparative study indicates that the new iterative segmentation algorithm provides acceptable results as seen in the tested examples of synthetics and satellite images.
The tracking algorithm is an important tool for motion analysis in computer vision. A new car tracking algorithm is proposed which is based on a new clipping technique in the field of adaptive filter algorithms. The u...
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The tracking algorithm is an important tool for motion analysis in computer vision. A new car tracking algorithm is proposed which is based on a new clipping technique in the field of adaptive filter algorithms. The uncertainty and occlusion of vehicles increase the noise in vehicle tracking in a traffic scene, so the new clipping technique can control noise in prediction of vehicle positions. The authors present a new quantised version of the LMS, namely the Qx-LMS algorithm, which has a better tracking capability in comparison with the clipped LMS (CLMS) and the LMS and also involves less computation. The threshold parameter of the Qx-LMS algorithm causes controllability and the increase of tracking and convergence properties, whereas the CLMS and LMS algorithms do not have these capabilities. The Qx-LMS algorithm is used for estimation of a noisy chirp signal, for system identification and in car tracking applications. Simulation results for noisy chirp signal detection show that this algorithm yields a considerable error reduction in comparison to the LMS and CLMS algorithms. The proposed algorithm, in tracking some 77 vehicles in different traffic scenes, shows a reduction of the tracking error relative to the LMS and CLMS algorithms.
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