• Title/Summary/Keyword: Clutter background

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SAR(Synthetic Aperture Radar) 3-Dimensional Scatterers Point Cloud Target Model and Experiments on Bridge Area (영상레이더(SAR)용 3차원 산란점 점구름 표적모델의 교량 지역에 대한 적용)

  • Jong Hoo Park;Sang Chul Park
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.1-8
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    • 2023
  • Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

Small Target Detection Method Using Bilateral Filter Based on Surrounding Statistical Feature (주위 통계 특성에 기초한 양방향 필터를 이용한 소형 표적 검출 기법)

  • Bae, Tae-Wuk;Kim, Young-Taeg
    • Journal of Korea Multimedia Society
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    • v.16 no.6
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    • pp.756-763
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    • 2013
  • Bilateral filter (BF), functioning by two Gaussian filters, domain and range filter is a nonlinear filter for sharpness enhancement and noise removal. In infrared (IR) small target detection field, the BF is designed by background predictor for predicting background not including small target. For this, the standard deviations of the two Gaussian filters need to be changed adaptively in background and target region of an infrared image. In this paper, the proposed bilateral filter make the standard deviations changed adaptively, using variance feature of mean values of surrounding block neighboring local filter window. And, in case the variance of mean values for surrounding blocks is low for any processed pixel, the pixel is classified to flat background and target region for enhancing background prediction. On the other hand, any pixel with high variance for surrounding blocks is classified to edge region. Small target can be detected by subtracting predicted background from original image. In experimental results, we confirmed that the proposed bilateral filter has superior target detection rate, compared with existing methods.

Real-Time Object Detection System Based on Background Modeling in Infrared Images (적외선영상에서 배경모델링 기반의 실시간 객체 탐지 시스템)

  • Park, Chang-Han;Lee, Jae-Ik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.4
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    • pp.102-110
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    • 2009
  • In this paper, we propose an object detection method for real-time in infrared (IR) images and PowerPC (PPC) and H/W design based on field programmable gate array (FPGA). An open H/W architecture has the advantages, such as easy transplantation of HW and S/W, support of compatibility and scalability for specification of current and previous versions, common module design using standardized design, and convenience of management and maintenance. Proposed background modeling for an open H/W architecture design decreases size of search area to construct a sparse block template of search area in IR images. We also apply to compensate for motion compensation when image moves in previous and current frames of IR sensor. Separation method of background and objects apply to adaptive values through time analysis of pixel intensity. Method of clutter reduction to appear near separated objects applies to median filter. Methods of background modeling, object detection, median filter, labeling, merge in the design embedded system execute in PFC processor. Based on experimental results, proposed method showed real-time object detection through global motion compensation and background modeling in the proposed embedded system.

Small Target Detection Using 3-dimensional Bilateral Filter (3차원 양방향 필터를 이용한 소형 표적 검출)

  • Bae, Tae-Wuk
    • Journal of Korea Multimedia Society
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    • v.16 no.6
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    • pp.746-755
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    • 2013
  • This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.

Real-time Small Target Detection using Local Contrast Difference Measure at Predictive Candidate Region (예측 후보 영역에서의 지역적 대비 차 계산 방법을 활용한 실시간 소형 표적 검출)

  • Ban, Jong-Hee;Wang, Ji-Hyeun;Lee, Donghwa;Yoo, Joon-Hyuk;Yoo, Seong-eun
    • Journal of Korea Society of Industrial Information Systems
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    • v.22 no.2
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    • pp.1-13
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    • 2017
  • In This Paper, we find the Target Candidate Region and the Location of the Candidate Region by Performing the Morphological Difference Calculation and Pixel Labeling for Robust Small Target Detection in Infrared Image with low SNR. Conventional Target Detection Methods based on Morphology Algorithms are low in Detection Accuracy due to their Vulnerability to Clutter in Infrared Images. To Address the Problem, Target Signal Enhancement and Background Clutter Suppression are Achieved Simultaneously by Combining Moravec Algorithm and LCM (Local Contrast Measure) Algorithm to Classify the Target and Noise in the Candidate Region. In Addition, the Proposed Algorithm can Efficiently Detect Multiple Targets by Solving the Problem of Limited Detection of a Single Target in the Target Detection method using the Morphology Operation and the Gaussian Distance Function Which were Developed for Real time Target Detection.

Study of Improvement of GMTI Performance Using DPCA and ATI (DPCA-ATI 결합을 이용한 GMTI 성능 향상에 대한 연구)

  • Lee, Myung-Jun;Lee, Seung-Jae;Lim, Byoung-Gyun;Oh, Tae-Bong;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.2
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    • pp.83-92
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    • 2018
  • Using ground moving target indicators equipped with synthetic aperture radars for locating moving targets within a wide background clutter in a short time is an excellent method for monitoring traffic. Although the displaced phase center antenna (DPCA) technique and along track interferometry (ATI) are real time methods with low computational complexity, they are essential for reducing cases of false alarm that can result in poor performance. In this paper, we propose two detection methods using DPCA and ATI-the parallel fusion method and serial fusion method. Simulation results demonstrate that the proposed detection methods are characterized by low probability of false alarm along with good performance. In particular, the serial fusion method possesses high detection probability along with low probability of false alarm (1/5th of the false alarm probability of the DPCA technique).

Velocity Estimation of Moving Targets on the Sea Surface by Azimuth Differentials of Simulated-SAR Image

  • Yang, Chang-Su;Kim, Youn-Seop;Ouchi, Kazuo
    • Korean Journal of Remote Sensing
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    • v.26 no.3
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    • pp.297-304
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    • 2010
  • Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

Fast Reference Region Adjustment Using Sizing Factor Generation in Correlation-Based Image Tracking

  • Sung, Si-Hun;Chien, Sung-Il
    • Journal of Electrical Engineering and information Science
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    • v.3 no.2
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    • pp.230-238
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    • 1998
  • When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.

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A Robust Multi-part Tracking of Humans in the Video Sequence (비디오 영상내의 사람 추적을 위한 강인한 멀티-파트 추적 방법)

  • 김태현;김진율
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2088-2091
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    • 2003
  • We presents a new algorithm for tracking person in video sequence that integrates the meanshift iteration procedure into the particle filtering. Utilizing the nice property of convergence to the modes in the meanshift iteration we show that only a few sample points are sufficient, while in general the particle filtering requires a large number of sample points. Multi-parts of a person is tracked independently of each other based on the color Then, the similarity against the reference model color and the geometric constraints between multi-parts are reflected as the sample weights. Also presented is the computer simulation results, which show successful tracking even for complex background clutter.

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Robust Detection and Tracking for a High-speed and Small Approaching Target in Clutter (클러터 환경에 강인한 고속/소형의 접근 표적 탐지/추적)

  • Kim, Ji-Eun;Noh, Chang-Kyun;Lee, Boo-Hwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.4
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    • pp.676-683
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    • 2011
  • In this paper, we propose a robust method which can detect and track a high-speed small approaching target in a cluttered environment for Korean Active Protection System. The proposed method uses a temporal and spatial filter, tracking filter to detect and track a single target in consecutive order. And it is comprised of a candidate target detection step, a prior target selection step and a target tracking. Field tests on real infrared image sequences show that the proposed method could stably track a high speed and small target in complex background and target occlusion.