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Noise adaptive switching median-based filter for impulse noise removal from extremely corrupted images

IET IMAGE processing 2011年第5期5卷 472-480页

作者： Fabijanska, A. Sankowski, D. Tech Univ Lodz Dept Comp Engn PL-90924 Lodz Poland

In this study an approach to impulse noise removal is presented. The introduced algorithm is a switching filter which identifies the noisy pixels and then corrects them by using median filter. In order to identify pixels corrupted by noise an analysis of local intensity extrema is applied. Comprehensive analysis of the algorithm performance [in terms of peak signal-to-noise ratio (PSNR) and Structural SIMilarity (SSIM) index] is presented. Results obtained on wide range of noise corruption (up to 98%) are shown and discussed. Moreover, comparison with well-established methods for impulse noise removal is provided. Presented results reveal that the proposed algorithm outperforms other approaches to impulse noise removal and its performance is close to ideal switching median filter. For high noise densities, the method correctly detects up to 100% of noisy pixels.

关键词： median filters extreme corrupted image noisy pixels noise adaptive switching median-based filter SSIM image denoising Computer vision and image processing techniques adaptive filters noise density impulse noise removal PSNR filtering methods in signal processing Optical, image and video signal processing structural similarity peak signal-to-noise ratio comprehensive analysis

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Removal of non-uniform complex and compound shadows from textured surfaces using adaptive directional smoothing and the thin plate model

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IET IMAGE processing 2011年第3期5卷 233-248页

作者： McFeely, R. Hughes, C. Jones, E. Glavin, M. Natl Univ Ireland Connaught Automot Res Grp Coll Engn & Informat Galway Ireland Valeo Vis Syst Tuam Co Galway Ireland

In this study, the authors propose a novel algorithm for removing complex shadows from textured surfaces within a single image. Previous shadow removal methods have attempted to solve this problem under a range of criteria, such as the type and number of light sources and shadow structure. Some methods require that the shadow umbra and penumbra be well defined. They have been shown to work best when the umbra is relatively large and when the penumbra is of a limited size and shape. However, these methods can fail if the shadow shape or form diverges from the norm. Many methods also require user intervention to locate whole or parts of the shadow. The authors propose a flexible shadow removal model which is capable of functioning without these limiting assumptions, or the need for user intervention. It is also capable of dealing with shadows cast on a wide range of textured surfaces. It uses a directional differential filter along with directional smoothing to find the shadow and a thin plate reconstruction model to remove shadows from an image surface. Results have shown that the proposed algorithm generates high-quality shadow-free images over a range of scenarios, such as multiple light sources, occlusions and textures.

关键词： nonuniform complex shadow removal textured surfaces thin plate model directional differential filter Computer vision and image processing techniques adaptive directional smoothing nonuniform compound shadow removal filtering methods in signal processing image texture Optical, image and video signal processing filtering theory smoothing methods

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Dual optimal filters for parameter estimation of a multivariate autoregressive process from noisy observations

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IET signal processing 2011年第5期5卷 471-479页

作者： Jamoos, A. Grivel, E. Shakarneh, N. Abdel-Nour, H. Al Quds Univ Dept Elect Engn Jerusalem Israel Univ Bordeaux 1 Equipe Signal & Image UMR CNRS IMS Dpt LAPS 5218 F-33405 Talence France

This study deals with the estimation of a vector process disturbed by an additive white noise. When this process is modelled by a multivariate autoregressive (M-AR) process, optimal filters such as Kalman or H-infinity filter can be used for prediction or estimation from noisy observations. However, the estimation of the M-AR parameters from noisy observations is a key issue to be addressed. Off-line or iterative approaches have been proposed recently, but their computational costs can be a drawback. Using on-line methods such as extended Kalman filter and sigma-point Kalman filter are of interest, but the size of the state vector to be estimated is quite high. In order to reduce this size and the resulting computational cost, the authors suggest using dual optimal filters. In this study, the authors propose to extend to the multi-channel case the so-called dual Kalman or H-infinity filters-based scheme initially proposed for single-channel applications. The proposed methods are first tested with a synthetic M-AR process and then with an M-AR process corresponding to a mobile fading channel. The comparative simulation study the authors carried out with existing techniques confirms the effectiveness of the proposed methods.

关键词： online methods white noise autoregressive processes parameter estimation H∞ filter iterative approaches multichannel case state vector Filters and other networks single-channel applications additive white noise mobile fading channel filtering methods in signal processing noisy observations Kalman filters extended Kalman filter multivariate autoregressive process signal processing theory M-AR parameters dual optimal filters vector process estimation sigma-point Kalman filter Other topics in statistics

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Target detection in high-resolution sea clutter via block-adaptive clutter suppression

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IET RADAR SONAR AND NAVIGATION 2011年第1期5卷 48-57页

作者： Shi, Y. -L. Shui, P. -L. Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

Attentions have been focused on the moving target detection in a high-resolution sea clutter. This study commences with a proposal of median-based estimator to estimate the power spectrum of high-resolution sea clutter by the time series observed in adjacent range cells and time intervals. The estimator provides a robust estimation when just a few aberrant time series happen in observation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF) is designed to suppress the clutter prior to the pulse integration. Then, the residual clutter, the output of the BACSF, is modelled as spherically invariant random vector. Upon applying an adaptive normalised matched filter (ANMF) to the residual clutter, a residual clutter's ANMF detector is derived. Moreover, in high-resolution radar background, considering that the approximately stationary intervals of sea clutter and residual clutter are much shorter than the coherent processing interval, another heuristic block-ANMF detector is proposed. It can integrate more pulses and can achieve better performance than the ANMF detector does. This study concludes with the experiments of simulated target against the real sea clutter. The experimental results demonstrate that, when target's Doppler frequency is beyond strong clutter region, the ANMF detector and block-ANMF detector perform better in the residual clutter than in the clutter.

关键词： Electromagnetic compatibility and interference adaptive normalised matched filter power spectrum estimate ANMF detector Optical, image and video signal processing high-resolution sea clutter Other topics in statistics matched filters Radar equipment, systems and applications radar resolution filtering methods in signal processing target detection pulse integration coherent processing interval median-based estimator block-adaptive clutter suppression radar clutter object detection robust estimation Doppler frequency radar detection high-resolution radar background time series interference suppression

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New efficient window function, replacement for the Hamming window

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IET signal processing 2011年第5期5卷 499-505页

作者： Mottaghi-Kashtiban, M. Shayesteh, M. G. Urmia Univ Dept Elect Engn Orumiyeh Iran Sharif Univ Technol Wireless Res Lab ACRI Dept Elect Engn Tehran Iran

A new simple window function is presented, which for the same window order (M), has a main-lobe width less than or equal to that of the Hamming window, while offering about 2-4.5 dB smaller peak side-lobe amplitude. Furthermore, just like the Hamming window, it is computationally efficient for signal spectrum analysis;this is because of the fact that, the sum of window coefficients with its shifted version by M/2 samples (i.e. 50% overlap) is constant for the overlapped region. The new window is obtained by adding the third harmonic of the cosine function to the Hamming window, and finding the appropriate amplitudes of DC term, cosine function, and its third harmonic to minimise the peak side-lobe amplitude. A comparison with the Kaiser and Dolph-Chebyshev windows is also performed. Finite impulse response filters designed by windowing method show the efficiency of the new window.

关键词： window order third harmonic filtering methods in signal processing DC term computationally efficient window function Hamming window signal processing Hamming codes cosine function finite impulse response filters side-lobe amplitude FIR filters Dolph-Chebyshev windows signal spectrum analysis signal processing theory Kaiser windows Codes

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Adaptive decision-feedback generalised sidelobe canceller against desired signal and interference non-stationarity

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IET signal processing 2011年第5期5卷 488-498页

作者： Lee, Y. Shieh, H. -W. Natl Chi Nan Univ Grad Inst Commun Engn Puli Nantou County Taiwan

Adaptive generalised sidelobe canceller (GSC) implemented with the least-mean-square (LMS) algorithm is a well-proven approach to effectively suppress unwanted interference. However, when the directions-of-arrival (DOAs) of the desired signal and interference sources change over time, its performance may be largely degraded because of the fact that not only the interference-cancelling filter of GSC does not properly cancel the 'moving' interference, but also both the signal-matched filter and blocking matrix of GSC deviate from their best states for the 'moving' desired signal. Recently, a robust adaptive decision-feedback (DF) GSC has been proposed to partly solve the problem, but if the DOAs of all sources vary significantly and continuously, the adaptive DFGSC will eventually lose track of the source motion. In this study, the authors present a new modification for the DFGSC structure, which provides additional robustness in this kind of non-stationary signal environment. Specifically, they extend the use of Householder transformation together with the LMS algorithm for DFGSC, and a new update method is introduced for the whole beamforming processor. In addition, the tracking behaviour of this specially designed adaptive structure is studied and analysed, leading to the derivation of optimal step size for the interference-cancelling filter. Simulation results show that this modified adaptive DFGSC is very effective in mitigating the described non-stationary scenario.

关键词： adaptive decision-feedback generalised sidelobe canceller Electromagnetic compatibility and interference householder transformation filtering methods in signal processing Interpolation and function approximation (numerical analysis) interference non-stationarity directions-of-arrival blocking matrix interference suppression interference-cancelling filter signal-matched filter least-mean-square algorithm source motion matched filters beamforming processor direction-of-arrival estimation least mean squares methods adaptive generalised sidelobe canceller

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Switching median filter: advanced boundary discriminative noise detection algorithm

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IET IMAGE processing 2011年第7期5卷 598-610页

作者： Tripathi, A. K. Ghanekar, U. Mukhopadhyay, S. Indian Inst Technol Dept Elect & Elect Commun Engn Kharagpur 721302 W Bengal India Natl Inst Technol Kurukshetra Dept Elect & Commun Engn Kurukshetra 136119 Haryana India

A novel, efficient and simple impulse noise detector for switching median filter is proposed in this study. The proposed method compares the difference value of the current pixel with the brightest and the darkest pixels in its working window and uses the difference value to determine whether the current pixel is corrupted by impulse noise. To avoid the false alarm generated in this first stage, the candidate pixels are passed through a second stage using local statistics. This new technique can remove the impulsive noise from corrupted images (grey scale and colour) efficiently and requires no previous training and noise statistics or strength for that purpose. For performance evaluation, four impulse noise models (Ng and Ma, 2006) are considered and noise models 3 and 4 are generalised to expand its application. Proposed algorithm is blind to the noise model and the amount of noise introduced. Quantitative and qualitative analysis performed on standard images, show that proposed method can detect impulse noise very efficiently under a wide range (up to 90%) of noise density. The proposed method performs well in terms of low miss and false detection and high peak-signal-to-noise ratio (PSNR) value. In comparison to all examined algorithms, the proposed technique performs favourably and outperforms the competitors for all the noise models. The gain is most prominent in case of impulse noise having spread as in case of noise models 3 and 4 (Ng and Ma, 2006).

关键词： median filters quantitative analysis switching median filter signal detection peak-signal-to-noise ratio qualitative analysis signal processing theory impulse noise detector impulse noise grey scale signal detection filtering methods in signal processing false detection boundary discriminative noise detection noise statistics corrupted images

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Tunable coplanar waveguide band-stop and band-pass filters based on open split ring resonators and open complementary split ring resonators

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IET MICROWAVES ANTENNAS & PROPAGATION 2011年第3期5卷 277-281页

作者： Velez, A. Aznar, F. Duran-Sindreu, M. Bonache, J. Martin, F. Univ Autonoma Barcelona Dept Elect Engn E-08193 Barcelona Spain

In this study, the authors show that open split ring resonators (OSRRs) and open complementary split ring resonators (OCSRRs) can be loaded with varactor diodes in order to implement tunable filters in coplanar waveguide (CPW) technology. By loading a CPW with shunt-connected varactor-loaded OSRRs, a band-stop filter with tunable central frequency results. The electronically tunable band stop can be switched to a pass band by replacing the shunt resonators with varactor-loaded OCSRRs. To illustrate the possibilities of the approach, a tunable band-stop filter and a tunable band-pass filter have been designed and fabricated. The measured characteristics are in good agreement with the co-simulations (electric and electromagnetic) and with the circuit simulations of the electric model. The measured tuning range is roughly 120% for the stop-band structure (for varying voltages between 0 and 28 V) and over 30% for the band-pass filter (for varying voltages between 5 and 25 V).

关键词： filtering methods in signal processing Waveguides and microwave transmission lines tunable filters resonator filters open split ring resonators coplanar waveguides varactor diodes tunable coplanar waveguide Capacitors varactors Waveguide and microwave transmission line components open complementary split ring resonators band-pass filters band-stop filters

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Particle filtering with correlated measurement and process noise at the same time

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IET RADAR SONAR AND NAVIGATION 2011年第7期5卷 726-730页

作者： Chen, J. Ma, L. Xian Polytech Univ Sch Comp Sci Xian 710048 Peoples R China Xidian Univ Sch Elect Engn Xian 710071 Peoples R China

Non-linear filter has been widely used in many applications, and particle filter (PF) is a promising approach because it can treat the non-linear and non-Gaussian system. If there are correlations between process noise and measurement noise in the non-linear system, the performance of general PF degenerates. The study addresses that there are correlated measurement and process noise at the same time in the non-linear system. Aiming at this problem, the authors decouple the correlation and rearrange the state transition equation to a new one, and remove the correlation. And then apply the general PF based on the new state transition equation and the original measurement equation. From the derivation, it is easy to know that the proposed method is equal to general PF when there are no correlated noises. Experimental results show that the proposed method outperforms the general PF when there are correlated noises.

关键词： filtering methods in signal processing nonlinear filter Gaussian processes noise correlation state transition equation correlated measurement particle filtering (numerical methods) signal processing theory nonGaussian system particle filtering process noise Other topics in statistics

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Accurate and efficient implementation of the time-frequency matched filter

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IET signal processing 2010年第4期4卷 428-437页

作者： O'Toole, J. M. Mesbah, M. Boashash, B. Univ Queensland Perinatal Res Ctr Herston Qld 4029 Australia Royal Brisbane & Womens Hosp UQ Ctr Clin Res Herston Qld 4029 Australia Qatar Univ Coll Engn Doha Qatar

The discrete time-frequency matched filter should replicate the continuous time-frequency matched filter, but the methods differ. To avoid aliasing, the discrete method transforms the real-valued signal to the complex-valued analytic signal. The theory for the time-frequency matched filter does not consider the discrete case using the analytic signal. The authors find that the performance of the matched filter degrades when using the analytic, rather than real-valued, signal. This performance degradation is dependent on the signal-to-noise ratio and the signal type. In addition, the authors present a simple algorithm to efficiently compute the time-frequency matched filter. The algorithm with the real-valued signal, comparative to using the analytic signal, requires one-quarter of the computational load. Hence the real-valued signal - and not the analytic signal - enables an accurate and efficient implementation of the time-frequency matched filter.

关键词： discrete time-frequency matched filter time-frequency analysis filtering methods in signal processing signal-to-noise ratio matched filters real-valued signal signal processing theory continuous time-frequency matched filter complex-valued analytic signal

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