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The multiple-model multi-Bernoulli (MM-MB) filter is a new attractive approach for estimating multiple maneuvering targets in the presence of clutter, missed detection and data association uncertainty. In this paper, we extend the Gaussian Mixture (GM) MM-MB filter to nonlinear models by using unscented transform techniques. Moreover, in order to improve the robustness and numerical stability of the...
Image scrambling is an important approach to cover image information. This paper presents a novel image scrambling algorithm based on two-dimensional discrete Henon map. In our algorithm, the parameters of Henon map are regarded as the key of scrambling, and image pixels are scrambled by iteration of the Henon map. The numerical experimental results show that the proposed algorithm has quite prominent...
Aiming for the denoising problem for infrared image, a novel algorithm is presented based on mixed statistical model in nonsubsampled contourlet domain. The noise coefficients which affect infrared image quality are generally considered to obey Gaussian distribution in nonsubsampled contourlet transform domain. At the same time, the original signal coefficients have the features of sharper peak at...
A novel, efficient image processing method is proposed here for extraction of pavement cracks from fuzzy and discontinuous pavement images. Pavement surface images obtained by CCD array, where pavement cracks are often blurry and discontinuous due to particle materials of pavement surface, crack degradation and unreliable crack shadows. Firstly, A series of preprocessing including using histogram...
Measurement censoring, or Tobit model censoring, is common in many engineering applications. It arises from limits in sensor dynamic range, and may be exacerbated by poor calibration of sensors. Censoring is often referred to as a clipped measurement or limit-of-detection discontinuity, and is represented as a piecewise-linear transform of the output variable. The slope of the piecewise-linear transform...
In this paper we propose an efficient approach for circular shape target recovery. The method makes use of the conterminous set of edge segments, or contour segments, instead of the huge edge points as traditional detectors do. First, the proposed approach computes the contour in a given image, which is then converted into contour segments at high curvature points. Then, by calculating the reinforcement...
This work investigates the problem of efficient signalling for optical wireless communication systems in the presence of signal-dependent noise. We propose a novel scheme based on signalling in the square-root domain (as defined by a square-root transform) where the optical channel originally distorted by signal-dependent noise is transformed into a stationary white Gaussian noise channel. The bit...
This paper proposes a dc error compensation algorithm using d-q synchronous coordinate transform phase-locked-loop in single-phase grid-connected converters. The DC errors are caused by the process of analog to digital conversion and the distorted grid voltage. The DC error can be remove by controlled the synchronous d-axis voltage using integral operation and digital infinite impulse response filter...
Modern autofocus systems are known for their fast response speed and optimized routines of the image processing. Nevertheless, the bottleneck of the autofocus system development is the transformation of the technical specification into the design rules that strictly take in account the specifications and introduce a guarantee of the best performance. In this paper we propose a new approach in autofocus...
Fluctuation pressure acting on the surface of high speed trains is the main source of aerodynamic noise. Therefore, it becomes very important to research components of the fluctuation pressure for controlling the aerodynamic noise. In this paper, Large Eddy Simulation (LES) method is applied to calculate the fluctuation pressure acting on a certain type of CRH high speed train and the distribution...
A new contourlet-based method is introduced for reducing noise in images corrupted by additive white Gaussian noise. This method takes into account the statistical dependencies among the contourlet coefficients of different scales. In view of this, a non-Gaussian multivariate distribution is proposed to capture the across-scale dependencies of the contourlet coefficients. This model is then exploited...
Compressive sensing system merges sampling and compression for a given sparse signal. It can reconstruct the image accurately by using fewer linear measurements than the original measurements. Hence, it is able to achieve reduction in complexity of sampling and number of computations. Since existing algorithms for implementation of sampling for the whole image are time consuming and it requires huge...
Statistical image modeling has attracted great attention in the field of image denoising. In this work, a new image denoising method in the contourlet domain is introduced in which the contourlet coefficients of images are modeled by using the Bessel k-form prior. A noisy image is decomposed into a low frequency approximation sub-image and a series of high frequency detail sub-images at different...
The appearance of masses in in X-ray mammograms is one of the early signs of women breast cancer. Currently, mammography is the single most effective and reliable technique in the investigation of breast abnormalities detection such as masses. However, their detection is still a challenging problem due, to the diversity in shape, size, ambiguous margins and to the poor contrast between the cancerous...
In this paper, a comparative study of different directional filters in the context of angiogram image enhancement has been discussed. Generally, the angiogram images acquired by the X-ray modality suffer from non-uniform illumination and noise. These artifacts are directional in nature and can be suppressed with the help of directional analysis. To cater this problem, we have presented a comparison...
This paper studies the feasibility of using the Radon transform to detect and orientate internal wave features from SAR images since it seems to be well suited for extracting quasi-linear features even at low signal-to-noise levels. The approach is based on the localized Radon transform where the intensity integration is performed over short line segments rather than across the entire image. The results...
The main purpose of this paper is to provide some additional insight into the several methods of cochannel blind signal separation that are based on the established concept of Independent Component Analysis (ICA). We compare published versions with a robust algorithm that has been devised and developed by the author. Most ICA algorithms are based on maximising the magnitudes of auto-cumulants and/or...
We describe a method for textural feature extraction of MRI volumes of the brain and, based upon those features, a method for classification and assessment of the anatomical malformations of the brain, due to Alzheimer's Disease (AD). In our research, we make the hypothesis that there is enough detectable textural evidence from a 3D analysis of MR images of the brain to detect and identify the earliest...
This paper presents new results on critical band masked distortion controlled quantisation of a linear transform representation of speech. In particular, fixed rate split vector quantisation of a critical band gain vector is investigated. While shown to be objectively significant in meeting masked distortion criteria, near-transparent quantisation of the critical band gain spectrum is nonetheless...
In this paper a new variation of Hough Transform is proposed. It can be used to detect shapes or curves in an image, with better accuracy, especially in noisy images. It is based on a fuzzy split of the Hough Transform parameter space. The parameter space is split into fuzzy cells which are defined as fuzzy numbers. This fuzzy split of the parameter space provides the advantage to use the uncertainty...
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