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Volume 143
Issue 3
IEE Proceedings - Vision, Image and Signal Processing
Volume 143, Issue 3, June 1996
Volumes & issues:
Volume 143, Issue 3
June 1996
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- Author(s): O. Tanrikulu and J.A. Chambers
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 137 –142
- DOI: 10.1049/ip-vis:19960449
- Type: Article
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p.
137
–142
(6)
Convergence and steady-state analyses of a least-mean mixed-norm adaptive algorithm are presented. This is formed as a convex mixture of the mean-square and the mean-fourth cost functions. The local exponential stability of the algorithm is shown by application of the deterministic averaging analysis and the total stability theorem. A theoretical misadjustment expression is then obtained by using the ordinary-differential-equation method. Simulation studies are presented to support the theoretical findings. The results demonstrate the advantage of mixing error norms in adaptive filtering when the measurement noise is composed of a linear combination of long-tail and short-tail noise distributions. - Author(s): A. Hasib and K. Hacioglu
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 143 –148
- DOI: 10.1049/ip-vis:19960367
- Type: Article
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p.
143
–148
(6)
The conventional linear predictive analysis in pulse-based coders is replaced by the so-called source-combined linear predictive method to match the excitations considered in two steps: synthesis filter determination and excitation search. It differs from Atal's two-pass approach in that the synthesis filter is optimised jointly with the excitation prior to the ABS excitation search. However, it is a difficult task to obtain the optimum solution, and, thus, a suboptimal algorithm is developed. Initially, the algorithm starts with the covariance method and then corrects the synthesis filter using an estimate of the excitation. This is accomplished by using two coupled equations originally developed. The effectiveness of the approach in multipulse and regular pulse excited coders is demonstrated. Extensive simulation results, at several bit rates, with different excitations, are presented. Comparisons are made with the standard coder and the coder that employs Atal's approach. In all conditions, the proposed coder is found to give better results. - Author(s): T.T. Le and J.S. Mason
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 149 –154
- DOI: 10.1049/ip-vis:19960447
- Type: Article
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p.
149
–154
(6)
A multilayer perceptron (MLP) is applied as a time domain nonlinear filter to two classes of degraded speech, namely gaussian white noise and nonlinear system degradation introduced by a low bit-rate CELP coder. The goal of the study is to examine the influence of the inherent nonlinearity within the MLP, and this is achieved by varying the levels of nonlinearity within the structure. Direct comparisons of MLPs and linear filters show that with CELP degradation the SNR improvements achieved by the MLP is measurably better than with an equivalent linear structure (3 dB cf 1.5 dB) but when the degradation is additive noise the two structures perform equally well. The study highlights the importance of scaling to achieve optimum performance, and of matching the enhancer to the degradation. - Author(s): K.H. Tan and M. Ghanbari
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 155 –163
- DOI: 10.1049/ip-vis:19960408
- Type: Article
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p.
155
–163
(9)
A classification scheme for an adaptive one- or two-dimensional discrete cosine transform (1-D/2-D DCT) technique is described and demonstrated to be a more appropriate strategy than the conventional 2-D DCT for coding motion compensated prediction error images. Two block-based classification methods are introduced and their accuracy in predicting the correct transform type discussed. The accuracy is assessed with a classification measure designed to ascertain the effectiveness of energy compaction when the predicted transform class is applied; vis-a-vis horizontally, vertically or two-dimensionally transformed blocks. Energy compaction is a useful property not only for efficient entropy coding but also for enhancing the resilience of the transform coder to quantisation noise. Improvements against the homogeneous 2-D DCT system both in terms of peak signal to noise ratio and subjective assessments are achieved. Observable ringing artifacts along edges, which are usual in conventional transform coding, are reduced. - Author(s): S.M.M. de Faria and M. Ghanbari
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 164 –170
- DOI: 10.1049/ip-vis:19960514
- Type: Article
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p.
164
–170
(7)
A low bit-rate video coding technique that uses spatio-temporal geometric transforms is presented. Motion compensation based on the bilinear transform is employed to reduce the temporal redundancy of the video. The spatial redundancy of the motion compensated error images is reduced by a combination of fractal and DCT. It is shown that in the objects boundaries of the motion compensated error image fractal outperforms DCT, while in the smooth areas DCT is better than fractal. A hybrid combination of fractal and DCT gives the best result. The performance of this hybrid codec with geometrically transformed motion compensation is compared against the H.261 standard video codec at 64 kbit/s. - Author(s): G.R. Wilson
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 171 –176
- DOI: 10.1049/ip-vis:19960320
- Type: Article
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p.
171
–176
(6)
The author describes how morphological operations using a square structuring element may be performed on a binary image by processing the crack code descriptions of the outlines. The operations of erosion, dilation, thinning, and fattening are described. - Author(s): K.K. Delibasis ; P.E. Undrill ; G.G. Cameron
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 177 –183
- DOI: 10.1049/ip-vis:19960513
- Type: Article
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p.
177
–183
(7)
Stack filters are a class of nonlinear spatial operators used for noise suppression. Their design is formulated as an optimisation problem and genetic algorithms (GAs) are used to perform the configuration. Applying the mean absolute error (MAE) as the basis of an objective function, the stack filter is used to restore magnetic resonance (MR) images corrupted with uncorrelated additive noise from 10% and 50%. The filter is trained on corresponding patches of the original and noisy image and then applied to the whole image. The outcomes are compared with the median filter and return a smaller MAE for all noise levels. The dependency of MAE on training window size and GA early termination is examined, showing that a reduction of 75% in computational complexity can be achieved by a 10% relaxation in MAE. The design is then extended from 9-point to 13-point filters and by training on Poisson noise, the filter is applied to nuclear medicine bone scans where no absolute truth exists. Surface topology, image profiles and the measurement of relative contrast show its value in reducing noise whilst preserving contrast. Because of its computational complexity the process has been implemented as a distributed GA using the parallel virtual machine (PVM) software. - Author(s): V.L. Narayana Murthy and A. Makur
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 184 –190
- DOI: 10.1049/ip-vis:19960515
- Type: Article
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p.
184
–190
(7)
The transformation technique is a powerful tool for designing 2-D FIR filters. However, it is not useful for the design of specially shaped filters with passband/stopband regions not centred around the origin. The authors extend this technique to design two types of filters. A notch filter has a stopband centred about a small region in the 2-D frequency plane. The authors propose an extension to the transformation technique with the windowing concept to achieve the design of notch filters. A directional filter has a passband extending fully along a straight line passing through the origin. The transformation technique is further extended to yield such directional filters. Design and application examples for both these filters are also presented. - Author(s): M. Umasuthan and A.M. Wallace
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 3, p. 191 –200
- DOI: 10.1049/ip-vis:19960407
- Type: Article
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p.
191
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(10)
Algorithms for the segmentation and description of range images are very sensitive to errors in the source data caused by noise processes in the optoelectronic sensing, and outliers caused by incorrect signal detection, for example false peaks in an active laser triangulation system. The authors present an approach to range data processing designed to reconstruct the underlying shape of the surfaces in the scene, yet preserve the discontinuities between them. The approach has two stages, first outlier removal by a lower complexity variation of the least median of squares estimator, and second, robust smoothing by anisotropic diffusion. To evaluate the proposed methods, the authors quantify the improvement in depth, normal and curvature estimation, and show how preprocessing improves surface patch segmentation and classification.
Convergence and steady-state properties of the least-mean mixed-norm (LMMN) adaptive algorithm
Source combined linear predictive analysis in pulse-based speech coders
Artificial neural networks for nonlinear time-domain filtering of speech
Block classification for an adaptive 1-D/2-D DCT video coding
Low bit-rate video coding with spatio-temporal geometric transforms
Morphological operations on crack coded binary images
Genetic algorithm implementation of stack filter design for image restoration
Design of some 2-D filters through the transformation technique
Outlier removal and discontinuity preserving smoothing of range data
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