Piet B. W. Schwering · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
The detection of small targets in maritime infrared surveillance is hampered by the presence of clutter. Sea surface structure, reflection and emission changes related to incident angle variations and surface effects are standard features governing the clutter behavior. Also special effects as sun glint and horizon effects play an important role for clutter. In order to optimize the detection process, quantitative clutter estimates are of use for filter settings. We have recorded a large amount of infrared backgrounds in the last few years, during common NATO trials. A large amount of different meteorological conditions took place during the various experiments. A first set of these data have been analyzed to obtain statistical data that represent the infrared scene. We have derived vertical temperature profiles, vertical fluctuation profiles, horizontal correlation coefficients and temporal correlation functions. In this paper we present the first analysis of these data. We are in the process of obtaining a condensed database of information to regenerate clutter images from bulk meteo parameters, and clutter parameters. The clutter and meteo parameters have been used to simulate various infrared scenes. Examples of this simulation process are shown in the presentation. The simulated images are statistically similar to the original images that were used to derive the parameters. A description of the image- generation is presented. Future expansions of the model are discussed.
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B. D. Green, W. T. Rawlins, L. G. Piper et al. · 1998
'■££8Q 4 'This technical report has been reviewed and is approved for publication. A£W»> r nc'^piv/Jt
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Ralph Zirkind · Applied Optics · 1982
Get PDF Email Share Share with Facebook Tweet This Post on reddit Share with LinkedIn Add to CiteULike Add to Mendeley Add to BibSonomy Get Citation Copy Citation Text Ralph Zirkind, "Correlation of infrared background clutter," Appl. Opt. 21, 173-174 (1982) Export Citation BibTex Endnote (RIS) HTML Plain Text Citation alert Save article
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Sidi Niu · 2009
Accurate statistical models for hyperspectral image (HSI) data distribution are useful for many applications. These models provide the foundation for development and evaluation of reliable algorithms for detection, classification, clustering, and estimation. It is well known that real world HSI data exhibit heavy tail due to nonhomogeneity. While the multivariate normal distribution is often used for multidimensional modeling, this distribution exhibits some limitations in capturing the heavy tail behavior of HSI data. In this thesis, a family of multivariate elliptically contoured distributions (ECDs) is investigated as an extension to well-known multivariate normal distribution, which gives more freedom in accurately capturing the decay rate and maintains most of appealing properties of multivariate normal distribution. The procedure to obtain the valid theoretical probability density function (PDF) of an ECD and methods to generate synthetic elliptically contoured random vector data are presented in detail. In order to test the symmetry assumption of real data, several graphical plots including scatter plots, t plots and beta plots; plots are proposed in terms of some invariant statistics under orthogonal transformations. These symmetry tests are applied to both symmetric and non-symmetric synthetic data as well as to real data from the AVIRIS sensor. Correlation coefficients which are numerical measures of detecting deviation from symmetry are also calculated as an auxiliary metric as part of these graphical tools. A weighted mixture of multivariate t distributions is proposed to model the main body and heavy tail Mahalanobis distribution of real data using an Exceedance Metric in a logarithmic scale. Expectation-Maximization (EM) and Stochastic Expectation-Maximization (SEM) methods for clustering multimodal data into several unimodal clusters are also included for completeness.
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Niu, Sidi · Digital Repository Service (Northeastern University)
Accurate statistical models for hyperspectral image (HSI) data distribution are useful for many applications. These models provide the foundation for development and evaluation of reliable algorithms for detection, classification, clustering, and estimation. It is well known that real world HSI data exhibit heavy tail due to nonhomogeneity. While the multivariate normal distribution is often used for multidimensional modeling, this distribution exhibits some limitations in capturing the heavy tail behavior of HSI data. In this thesis, a family of multivariate elliptically contoured distributions (ECDs) is investigated as an extension to well-known multivariate normal distribution, which gives more freedom in accurately capturing the decay rate and maintains most of appealing properties of multivariate normal distribution. The procedure to obtain the valid theoretical probability density function (PDF) of an ECD and methods to generate synthetic elliptically contoured random vector data are presented in detail. In order to test the symmetry assumption of real data, several graphical plots including scatter plots, t plots and beta plots; plots are proposed in terms of some invariant statistics under orthogonal transformations. These symmetry tests are applied to both symmetric and non-symmetric synthetic data as well as to real data from the AVIRIS sensor. Correlation coefficients which are numerical measures of detecting deviation from symmetry are also calculated as an auxiliary metric as part of these graphical tools. A weighted mixture of multivariate t distributions is proposed to model the main body and heavy tail Mahalanobis distribution of real data using an Exceedance Metric in a logarithmic scale. Expectation-Maximization (EM) and Stochastic Expectation-Maximization (SEM) methods for clustering multimodal data into several unimodal clusters are also included for completeness.
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Qichao Cui, Chao Ji, Yuanhong Yu et al. · 2024
Earth-sea clutter is a significant component of radar signals and can significantly impair radar performance. Radar clutter suppression is an essential aspect of radar signal detection. The realistic modelling and simulation of radar clutter can assist in the identification of more effective radar clutter suppression algorithms. The present paper introduces a more comprehensive radar clutter model and presents the simulation signal of the radar clutter amplitude statistics and spectral characteristics. The aim of this study was to address the issue of a high false alarm rate associated with the traditional constant false-alarm rate (CFAR) detection method when the clutter changes drastically in the airspace. To this end, a background adaptive clutter map constant false alarm detection method based on the clutter environment characteristics of the adaptive change of iteration coefficients was proposed and its efficacy was demonstrated through experimental results. The results demonstrate that the background adaptive clutter map constant false alarm detection method proposed in this paper is capable of effectively suppressing ground and sea clutter, thereby meeting the engineering requirements.
Cited by 2
Min Li, Xinnan Fan, Xuewu Zhang et al. · 2016
Without priori information, anomaly detector has more important utility compared with supervised target detection. Many classical anomaly detectors have obtained perfect performance in many situations. However, there still have two problems which are correlated with accuracy of anomaly detector. Firstly, clutter background induced more and more difficult pixel which have moderate statistical difference. Then, ideal uncontaminated subset of clutter background is hard to be obtain which is used to estimate background model. Secondly, difference of spectral content of different background objects will effect salience of anomaly targets. And it is arbitrary that uncertain pixels is nominated as non-anomalies by one threshold. For above two problems, a multi-aperture anomaly detector is proposed in this paper. Without selection of anomaly-free pixels and accurate statistical model, the proposed anomaly detector is expected to decrease false alarm rate with clutter background. A multi-aperture division for hyperspectral cube is conducted by iterative process. Statistical data of ever subaperture will be named as basis, which represent spectral characteristic of a certain range of spectral cube. Then, anomaly salience is proposed to measure the difference between pixels and sub-aperture basis. On the other hand, continuity of membership value based on fuzzy logical theory is more suitable to nominate difficulty pixels which has moderate anomaly salience. At last defuzzification ruler can be used to fuse different detection results from multi-aperture.
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Heying, Adam · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2020
Abstract not provided.
Cited by 0Open access
Deepak Kumar Panda, Sukadev Meher · 2011
In this paper we propose a novel method for detecting target object in presence of background clutter such as leaves of trees and changing illumination condition in real-time video and then tracking the object. A small movement in the background such as leaves of trees and changing illumination condition affects the performance of the automated tracking system. Here in this paper, we reduce the spatial and intensity resolution of an image to minimize the effects caused by the background clutter. A 3-frame-differencing method is employed to detect a moving object. Fuzzy c-means clustering is used to segment the moving object from the background. The proposed method yields superior performance as compared to the other existing methods.
Cited by 8
Jeffrey J. Carlson · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2023
Methods for segmenting the reflected light of an illumination source having a characteristic wavelength from background illumination (i.e. clutter) in structured lighting systems can comprise pulsing the light source used to illuminate a scene, pulsing the light source synchronously with the opening of a shutter in an imaging device, estimating the contribution of background clutter by interpolation of images of the scene collected at multiple spectral bands not including the characteristic wavelength and subtracting the estimated background contribution from an image of the scene comprising the wavelength of the light source and, placing a polarizing filter between the imaging device and the scene, where the illumination source can be polarized in the same orientation as the polarizing filter. Apparatus for segmenting the light of an illumination source from background illumination can comprise an illuminator, an image receiver for receiving images of multiple spectral bands, a processor for calculations and interpolations, and a polarizing filter.
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III Reifenstein, von Thuena E. C., P. C. Blau et al. · 1963
Abstract : The instrumentation phase of an infrared back ground measurement program is summarized. Its objective is to obtain infrared background data from a U-2 aircraft that will assist in the de sign and evaluation of future space- based infra red detection systems. It is planned to measure the statistics of background clutter in the 1-3 micron region with 0.10 micron resolution for a variety of geometrical conditions of solar illumination and viewing and to measure solar spectra for a range of aircraft altitudes and solar elevations. This report, which covers the period from November 1962 to May 1963, deals with the instrumentation and data gathering aspects of the program.
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Tao Liu, Gong Yao-huan, Jie Wang et al. · 2009
External impulsive interference (IMI) will severely degrade the performance of an Over-the-horizon radar (OTHR), and detection and suppression of IMI in strong clutter environment is the prerequisite for the target detection. This paper proposes a novel method based on the signal subspace properties, aiming at effectively detecting IMI with easy or without clutter suppression. Selective survey on median eigenvalues variation and discarding two largest eigenvalues can suppress clutter and simultaneously show peaks indicating the IMI position, which can be viewed as a joint clutter suppression and interference detection. Its operational performance is evaluated using experimental data from a high frequency surface wave(HFSW) OTHR system.
Cited by 2
Maria Greco, Part A Maria Greco, Part B Frédéric Pascal · 2014
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Vivian George, Thomas W. Altshuler, Erik M. Rosen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
Most technologies in use or proposed for use to detect landmines and unexploded ordnance (UXO) suffer from unacceptably high false-alarm rates, even at modest probabilities of detection. High false-alarm rates are a consequence of the inability to discriminate real UXO and landmines from man-made and naturally occurring clutter. The goal of the Defense Advanced Research Project Agency (DARPA)- sponsored Background Clutter Data Collection Experiment is to provide data which will support the development of techniques that are more adept at discriminating UXO from benign, man- made objects. During the fall of 1996, high areal density site surveys were completed using the following sensor types: magnetometer, infrared, electromagnetic induction, and ground- penetrating radar. Preliminary analysis of the data confirmed that a large number of anomalies in the sensor data are visually indistinguishable from anomalies that are a result of emplaced inert UXO or landmines. The Firing Point 20 site at Fort A. P. Hill exhibits the largest number of these ordnance- like anomalies. To determine the source of a subset of these sensor response anomalies, a 1-week excavation effort was conducted. This paper presents an analysis of the data to determine the candidate locations for, the procedures used during, and the results of the excavation.
Cited by 1
Jinnan Gong, Yin Zhang, Qingyu Hou et al. · Infrared Physics & Technology · 2014
Cited by 19
Larry B. Stotts · 1986
Abstract : This report presents the maximum likelihood approach to nonmoving resolved/partially resolved target extraction from correlated images that can be extended to the underresolved, weak target case by restructuring the basic problem development in terms of the inherent two-dimensional aspects found in most remotely sensed images. The report also outlines the research required to extend application of the restructured development to an optimum processing approach for detecting stationary or slowly moving targets in clutter.
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Honghua Chang · 2008
According to the IR imaging system structure and the procedure of IR radiation transmission,the definition of background clutter was given,which was similar to the target signal in background. The two characteristics of background clutter were analyzed,which were feature-dependence and relativity. Background clutter had its impact on the target signal only through signal processing algorithm. The model of IR imaging system detection performance influenced by background clutter was obtained. Compared with the performance model without the consideration of background clutter,it is conclued that background clutter greatly enhance the difficulty of target detection. The system performance varies complexly with the difference between the targets and background in the mean values and variances.
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Karin Nordström (14500), Paul D Barnett (14501), David C O'Carroll (14502) · Figshare · 2015
<p>The pattern used in figure–ground experiments (A) contains components of random frequency and phase, with 1/f statistics similar to those of natural scenes. It excites HS tangential neurons maximally (average of five recordings [B]), but has no effect on most STMDs (STMD 1 [C]). The bars indicate peri-stimulus duration and the arrows the direction of clutter motion.</p>
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Leonid G. Dorosinskiy, A. A. Kurganski · Electronic scientific archive of UrFU (Ural Federal University) · 2017
The algorithm of multiple-unit target acquisition against the background of structurally similar disturbance and the method of algorithm analysis have been proposed. The proposed algorithm allows increasing of the signal detection accuracy within close sources of disturbances even in cases when disturbances are not set according to the angular coordinates.
Cited by 2Open access
Shujun Peng, Lingjiang Kong, Xiaobo Yang · 2011
This paper presents an improved algorithm, Zoning 2-D CFAR, for the detections in a non-homogeneous clutter background. Numerical results show that the false alarm rate is successfully controlled in the severe clutter environments.
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