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Volume 153
Issue 2
IEE Proceedings - Vision, Image and Signal Processing
Volume 153, Issue 2, April 2006
Volumes & issues:
Volume 153, Issue 2
April 2006
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- Author(s): C. Fu and B.J. Falkowski
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 87 –94
- DOI: 10.1049/ip-vis:20045248
- Type: Article
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(8)
New classes of linearly independent ternary arithmetic transforms in standard algebra called ternary arithmetic helix transforms are introduced. Four types of helix transform matrices with detailed recursive equations are shown. Various properties, mutual relationships among transform matrices and spectra as well as results of helix transforms for some special cases of ternary logic functions are discussed. Computational costs for the calculation of new transforms are also presented. - Author(s): A.T. Connie ; F. Ferdousi ; M. Sharmin ; M.R. Khan
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 95 –100
- DOI: 10.1049/ip-vis:20045254
- Type: Article
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95
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(6)
A simple and efficient method for system identification even at a very low signal-to-noise ratio (SNR) is presented. At an SNR as low as −7.5 dB, noise dominates the spectrum and system poles are almost lost in the profound noise. In the proposed method, an enhanced spectrum is estimated in the discrete cosine transform (DCT) domain using the least squares curve-fitting technique. The system modes that were previously indistinguishable become prominent in the enhanced spectrum. The system order is then overestimated using least squares higher order Yule–Walker (LSHOYW) equations to obtain better accuracy. The poles having higher strength in the autocorrelation domain are then identified as system poles. - Author(s): S. Mahmoodi and B.S. Sharif
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 101 –108
- DOI: 10.1049/ip-vis:20045205
- Type: Article
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101
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(8)
Noise reduction and time interval segmentation of a noise-contaminated piecewise continuous signal is considered by the authors as a non-linear optimisation problem. The mathematical framework of this method is presented both in continuous-time and discrete-time domains. The smoothed signal and segmented time intervals of the original noisy signal are calculated as an optimised solution for an energy functional. An algorithm similar to the level set method is developed to find the optimised solution. In this algorithm, the discontinuity points separating consecutive continuous signals are preserved while the noise is reduced. Therefore this method fundamentally exhibits a better performance compared with a traditional low-pass filter suppressing high frequency components, including discontinuity points. The results also demonstrate a better quality in noise reduction in comparison to the median and Gaussian filters. - Author(s): I. Tsiftzis ; I. Andreadis ; A. Elenas
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 109 –114
- DOI: 10.1049/ip-vis:20050068
- Type: Article
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109
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(6)
A new efficient technique for the classification of signals, in the form of earthquake-induced ground-acceleration time histories, according to the damage that they cause in buildings, is presented for the first time. A training set of real seismic accelerograms with well-known damage effects is utilised and fuzzy representations of prototype signals are extracted. These prototypes are selected with respect to the architectural and structural damage caused by the seismic-acceleration time histories. The classification of the unknown accelerograms takes place through a fuzzy comparison with the prototypes and each is classified to the most similar prototype. Real, seismic time–acceleration records were used for testing the algorithm and the high percentage of the correctly recognised signals prove the effectiveness of the algorithm. Correct classification rates of up to 84% are achieved. - Author(s): P. Gao ; W.L. Woo ; S.S. Dlay
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 115 –131
- DOI: 10.1049/ip-vis:20045174
- Type: Article
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115
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(17)
The problem of blind separation of independent sources in non-linear mixtures is considered and the focus of this work is on a new type of non-linear mixture in which a linear mixing matrix is sandwiched between two mutually reverse non-linearities. The demixing system culminates to a novel Weierstrass network that is shown to successfully restore the original source signals under the non-linear mixing conditions. The corresponding parameter learning algorithm for the proposed network is presented through formal mathematical derivation. The authors show for the first time a new result based on the theory of forward series and series reversion that is integrated into a neural network to implement the proposed demixer. Simulations, including both synthetic and recorded signals, have been carried out to verify the efficacy of the proposed method. It is shown that the Weierstrass network outperforms other tested independent component analysis (ICA) methods (linear ICA, radial-basis function and multilayer perceptron network) in terms of speed and accuracy. - Author(s): A. Yasotharan and T. Thayaparan
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 132 –140
- DOI: 10.1049/ip-vis:20045231
- Type: Article
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132
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(9)
In the continuous-time domain, maximum-likelihood (ML) detection of a chirp signal in white Gaussian noise can be done by maximising (with respect to signal parameter arguments) the line-integral transform (LIT) of the classical Wigner distribution (of the observed signal). The LIT is known variously as the Hough transform and the Radon transform. For discrete-time signals, the Wigner-type distribution defined by Claasen and Mecklenbrauker has become popular as a signal analysis tool. Moreover, it is commonly believed that ML detection of a discrete-time chirp signal in independent and identically distributed (i.i.d.) Gaussian noise can be done by maximising the LIT of the Wigner–Claasen–Mecklenbrauker distribution (WCMD). This belief is false and results in loss of performance. The authors derive a Wigner-type distribution for discrete-time signals such that ML detection of a discrete-time chirp signal in i.i.d. Gaussian noise can be done by maximising the LIT of this distribution. Simulated receiver operating curves showing the performance advantage of the new method over the WCMD-based method are provided. The signal parameter values that maximise the LIT are taken as estimates of the actual parameters. The authors provide simulation results showing that the parameter estimates obtained using the new method are more accurate than those obtained using the WCMD-based method. For the WCMD-based method, the range of unambiguously measurable frequencies (RUMF) is [−π/2, π/2]. For the new method, the RUMF is [−π, π]. - Author(s): J.-Y. Wu and C.-A. Lin
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 141 –148
- DOI: 10.1049/ip-vis:20045118
- Type: Article
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p.
141
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(8)
A method to construct an optimal finite impulse response (FIR) approximate inverse for discrete-time causal FIR periodic filters in the presence of measurement noise is proposed. The objective function to be minimised is the sum-of-mean-square errors over one period. On the basis of the matrix impulse response of the multi-input multi-output time-invariant representation of periodic filters, the optimisation problem is formulated as one that minimises the summed equation errors of a set of over-determined linear equations. It is shown that the problem is equivalent to a set of least-squares problems from which a simple, closed-form solution is obtained. Numerical examples are used to illustrate the performance of the proposed FIR approximate inverse. - Author(s): A.D. Spence and M.J. Chantler
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 149 –159
- DOI: 10.1049/ip-vis:20050229
- Type: Article
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p.
149
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(11)
The optimal placement of the illumination for three-image photometric stereo acquisition of smooth and rough surface textures with respect to camera noise is derived and verified experimentally. The sensitivities of the scaled surface normal elements are derived and used to provide expressions for the noise variances. An overall figure of merit is developed by considering the image-based rendering (i.e. relighting) of Lambertian surfaces. This metric is optimised numerically with respect to the illumination angles. An orthogonal configuration was found to be optimal. With regard to constant slant, the optimal separation between the tilt angles of successive illumination vectors was found to be 120°. The optimal slant angle was found to be 90° for smooth surface textures and 55° for rough surface textures. - Author(s): A.M. Wallace ; R.C.W. Sung ; G.S. Buller ; R.D. Harkins ; R.E. Warburton ; R.A. Lamb
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 160 –172
- DOI: 10.1049/ip-vis:20045023
- Type: Article
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p.
160
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(13)
A new multi-spectral laser radar (ladar) system based on the time-correlated single photon counting, time-of-flight technique has been designed to detect and characterise distributed targets at ranges of several kilometres. The system uses six separated laser channels in the visible and near infrared part of the electromagnetic spectrum. The authors present a method to detect the numbers, positions, heights and shape parameters of returns from this system, used for range profiling and target classification. The algorithm has two principal stages: non-parametric bump hunting based on an analysis of the smoothed derivatives of the photon count histogram in scale space, and maximum likelihood estimation using Poisson statistics. The approach is demonstrated on simulated and real data from a multi-spectral ladar system, showing that the return parameters can be estimated to a high degree of accuracy. - Author(s): K. Masselos ; Y. Andreopoulos ; T. Stouraitis
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 173 –180
- DOI: 10.1049/ip-vis:20045218
- Type: Article
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p.
173
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(8)
The two-dimensional discrete wavelet transform (2D DWT) is becoming one of the standard tools for image and video compression systems. Various input-traversal schedules have been proposed for its computation. Here, major schedules for 2D DWT computation are compared with respect to their performance on a very long instruction-word (VLIW) digital signal processor (DSP). In particular, three popular transform-production schedules are considered: the row–column, the line based and the block based. Realisations of the wavelet transform according to the considered schedules have been developed. They are parameterised with respect to filter pair, image size and number of decomposition levels. All realisations have been mapped on a VLIW DSP, as these processors currently form an attractive alternative for the realisation of signal, image and video processing systems. Performance metrics for the realisations for a complete set of parameters have been obtained and compared. The experimental results show that each realisation performs better for different points of the parameter space. - Author(s): B. Parys ; M.V. Papalexandris ; A. Cornet
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 181 –184
- DOI: 10.1049/ip-vis:20050192
- Type: Article
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p.
181
–184
(4)
The authors demonstrate the potential of femtosecond laser pulsed illumination and picosecond detection in biomedical imaging via an efficient and simple Monte Carlo laser pulse diffusion simulation, based on realistic biological parameters. The evolution of the contrast of a sinusoidal grid in a diffuse medium as a function of the width of a temporal gate is shown. - Author(s): L. Kaur ; R.C. Chauhan ; S.C. Saxena
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 185 –190
- DOI: 10.1049/ip-vis:20045168
- Type: Article
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p.
185
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(6)
An adaptive image-coding algorithm for compression of medical ultrasound (US) images in the wavelet domain is presented. First, it is shown that the histograms of wavelet coefficients of the subbands in the US images are heavy-tailed and can be better modelled by using the generalised Student's t-distribution. Then, by exploiting these statistics, an adaptive image coder named JTQVS-WV is designed, which unifies the two approaches to image-adaptive coding: rate–distortion (R–D) optimised quantiser selection and R–D optimal thresholding, and is based on the varying-slope quantisation strategy. The use of varying-slope quantisation strategy (instead of fixed R–D slope) allows coding of the wavelet coefficients across various scales according to their importance for the quality of reconstructed image. The experimental results show that the varying-slope quantisation strategy leads to a significant improvement in the compression performance of the JTQVS-WV over the best state-of-the-art image coder, SPIHT, JPEG2000 and the fixed-slope variant of JTQVS-WV named JTQ-WV. For example, the coding of US images at 0.5 bpp yields a peak signal-to-noise ratio gain of >0.6, 3.86 and 0.3 dB over the benchmark, SPIHT, JPEG2000 and JTQ-WV, respectively. - Author(s): C. Wang and Z. Ye
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 191 –198
- DOI: 10.1049/ip-vis:20045233
- Type: Article
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191
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(8)
A novel fusion scheme for volumetric medical imagery based on first-order local variational information is presented. The authors first define the contrast of a volumetric image with an arbitrary number of bands, which corresponds with the 3D gradient in the special case of a single-band image with a Euclidean metric. This contrast of multi-band image is regarded as the target contrast field. The next step is to look for a single-band volumetric image as the fusion result, which will have the closest gradient field to the contrast of the input multi-band image. It is a functional extremum problem. Using the variational approach, it leads directly to its Euler–Lagrange equation. By iteration of gradient descent, the final result can be obtained. Experimental results are presented to support the performance of the method. - Author(s): H. Proença and L.A. Alexandre
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 199 –205
- DOI: 10.1049/ip-vis:20050213
- Type: Article
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(7)
An overview of the iris image segmentation methodologies for biometric purposes is presented. The main focus is on the analysis of the ability of segmentation algorithms to process images with heterogeneous characteristics, simulating the dynamics of a non-cooperative environment. The accuracy of the four selected methodologies on the UBIRIS database is tested and, having concluded about their weak robustness when dealing with non-optimal images regarding focus, reflections, brightness or eyelid obstruction, the authors introduce a new and more robust iris image segmentation methodology. This new methodology could contribute to the aim of non-cooperative biometric iris recognition, where the ability to process this type of image is required. - Author(s): S. Intajag ; K. Paithoonwatanakij ; A.P. Cracknell
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 206 –214
- DOI: 10.1049/ip-vis:20045211
- Type: Article
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p.
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Object-based segmentation is the first essential step for image processing applications. 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. - Author(s): W.S. Lin ; Y.L. Gai ; A.A. Kassim
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 215 –223
- DOI: 10.1049/ip-vis:20050110
- Type: Article
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A method based upon subjective viewing tests to evaluate the perceptual impact of different extents of edge sharpness is presented and the most eye-pleasing sharpness (MEPS) for an image edge-sharpening process is derived. The findings with Laplacian of Gaussian edge-enhancement filter show that the baseline MEPS is about 2.6 times that of the local just-noticeable difference, and the actual MEPS is also dependent on the contrast increase in the surrounding areas. The proposed methodology can be used to determine the MEPS for a particular edge-enhancement process, and the resultant formulation for the perceptual impact of edge sharpness can be used for reference in control of edge enhancement, image reconstruction and de-blurring processing, as well as objective visual quality gauge. - Author(s): S. Bourennane and J. Marot
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 224 –229
- DOI: 10.1049/ip-vis:20050149
- Type: Article
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The application of the high-resolution methods of array processing to source localisation has led to a considerable improvement in results. By considering some conventions, these methods can be applied to the characterisation of straight lines in an image. It is proposed to associate a high-resolution method with a method that generates a signal out of an image. This approach permits, in particular, to estimate the parameter ‘offset’, that is, the intersection with the upper side of the image of the straight lines. The proposed approach is fast and efficient when compared with the well-known method ‘extension of the Hough transform’. - Author(s): X.-W. Yin ; M. Fleury ; A.C. Downton
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 230 –236
- DOI: 10.1049/ip-vis:20045151
- Type: Article
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(7)
Conditional probability to predict sub-block significance improves the peak signal-to-noise ratio (PSNR) performance of a block-set wavelet image coder. Adaptive scanning of sub-blocks results in a further gain in PSNR performance. Together, the related algorithmic changes introduced by the authors result in competitive PSNR performance without the need for an arithmetic coding stage. As a consequence, timing tests reveal that the critical decoder computational complexity is reduced. - Author(s): S. Benierbah and M. Khamadja
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 237 –243
- DOI: 10.1049/ip-vis:20050129
- Type: Article
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A new technique, called inter-band compensated prediction, for coding colour and multispectral images is presented. It is suitable to use for coding any spectral domain and can code colour and multispectral images with any number of bands. This technique is based on the same principles as the very efficient motion compensated prediction largely used in video coding. Thus, each band is predicted in the spectral direction by compensating the differences in the neighbouring bands and then coding the prediction error spatially by another method. This is a forward adaptive prediction and the information used for compensation is coded as side information with prediction error. The comparison of the coding results with the state-of-the-art coding algorithms, based on spectral transformations, proves that this technique is very efficient and can even outperform them. In addition, compensation can be combined with any spatial coder that allows lossless, lossy and scalable coding of any spectral content of the image. It has also the advantages of being simple to implement and to use with parallel architectures. - Author(s): J. Jiang ; J. Xia ; G. Xiao
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 2, p. 244 –252
- DOI: 10.1049/ip-vis:20050085
- Type: Article
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The authors describe an efficient algorithm design for lossless video compression by using MPEG-2 as a basic research platform. Starting from MPEG motion estimation and compensation, the proposed algorithm focuses on a context tree design to fine tune the statistics and thus optimise the estimation of conditional probabilities to drive an arithmetic coder. In comparison with the existing work on context tree design, the proposed algorithm features: (i) prefix sequence matching to locate the statistics model at the internal node nearest to the stopping point, where successful match of context sequence is broken; (ii) traversing the context tree along a fixed order of context structure with a maximum number of four motion compensated errors; and (iii) context thresholding to quantise the higher end of error values into a single statistics cluster. As a result, the proposed algorithm is able to achieve competitive processing speed, low computational complexity and high compression performances, which bridges the gap between universal statistics modelling and practical compression techniques. When JPEG-LS and CALIC, the existing state-of-the-art in lossless compression of still images, are applied to those motion compensated error-frames as well as individual non-predicted frames to formulate benchmarks, the authors' experiments illustrate that the proposed algorithm outperforms JPEG-LS by up to 24% and CALIC by up to 22%, yet the processing time ranges from less than 2 s per frame to 6 s per frame on a typical PC computing platform.
Linearly independent ternary arithmetic helix transforms, their properties and relations
Identification of AR parameters at a very low SNR using estimated spectral distribution in DCT domain
Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method
Fuzzy system for seismic signal classification
Non-linear independent component analysis using series reversion and Weierstrass network
Optimum time–frequency distribution for detecting a discrete-time chirp signal in noise
Optimal finite impulse response approximate inverse of linear periodic filters
Optimal illumination for three-image photometric stereo using sensitivity analysis
Detecting and characterising returns in a pulsed ladar system
Performance comparison of two-dimensional discrete wavelet transform computation schedules on a VLIW digital signal processor
Assessment of femtosecond temporal gating for imaging in biological medium by Monte Carlo simulations
Adaptive compression of medical ultrasound images
First-order fusion of volumetric medical imagery
Iris segmentation methodology for non-cooperative recognition
Iterative satellite image segmentation by fuzzy hit-or-miss and homogeneity index
Perceptual impact of edge sharpness in images
Estimation of straight line offsets by high-resolution method
Prediction and adaptive scanning in block-set wavelet image coder
Compression of colour images by inter-band compensated prediction
MPEG-2 based lossless video compression
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