• Title/Summary/Keyword: Aerial Image Sequence

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Recovering the Elevation Map by Stereo Modeling of the Aerial Image Sequence (연속 항공영상의 스테레오 모델링에 의한 지형 복원)

  • 강민석;김준식;박래홍;이쾌희
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.9
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    • pp.64-75
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    • 1993
  • This paper proposes a recovering technique of the elevation map by stereo modeling of the aerial image sequence which is transformed based on the aircraft situation. The area-based stereo matching method is simulated and the various parameters are experimentally chosen. In a depth extraction step, the depth is determined by solving the vector equation. The equation is suitable for stereo modeling of aerial images which do not satisfy the epipolar constraint. Also, the performance of the conventional feature-based matching scheme is compared. Finally, techniques analyzing the accuracy of the recovered elevation map (REM) are described. The analysis includes the error estimation for both height and contour lines, where the accuracy is based on the measurements of deviations from the estimates obtained manually. The experimental results show the efficiency of the proposed technique.

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Hybrid navigation parameter estimation from aerial image sequence (항공영상을 이용한 하이브리드 영상 항법 변수 추출)

  • 심동규;정상용;이도형;박래홍;김린철;이상욱
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.2
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    • pp.146-156
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    • 1998
  • Thispapr proposes hybrid navigation parameter estimation using sequential aerial images. The proposed navigation parameter estimation system is composed of two parts: relative position estimation and absolute position estimation. the relative position estimation recursively computes the current velocity and absolute position estimation. The relative position estimation recursively computes the current velocity and position of an aircraft by accumulating navigation parameters extracted from two succesive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameters as an aircraft goes on navigating. therefore absolute position estimation is required to compensate for position error generated in the relative position step. The absolute position estimation algorithm combining image matching and digital elevation model(DEM) matching is presented. Computer simulation with real aerial image sequences shows the efficiency of the proposed hybrial algorithm.

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Implementation of the Integrated Navigation Parameter Extraction from the Aerial Image Sequence Using TMS320C80 MVP (TMS320C80 MVP 상에서의 연속항공영상으리 이용한 통합 항법 변수 추출 시스템 구현)

  • Sin, Sang-Yun;Park, In-Jun;Lee, Yeong-Sam;Lee, Min-Gyu;Kim, Gwan-Seok;Jeong, Dong-Uk;Kim, In-Cheol;Park, Rae-Hong;Lee, Sang-Uk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.3
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    • pp.49-57
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    • 2002
  • In this paper, we deal with a real time implementation of the integrated image-based navigation parameter extraction system using the TMS320C80 MVP(multimedia video processor). Our system consists of relative position estimation and absolute position compensation, which is further divided into high-resolution aerial image matching, DEM(Digital elevation model) matching, and IRS (Indian remote sensing) satellite image matching. Those algorithms are implemented in real time using the MVP. To achieve a real-time operation, an attempt is made to partition the aerial image and process the partitioned images in parallel using the four parallel processors in the MVP. We also examine the performance of the implemented integrated system in terms of the estimation accuracy, confirming a proper operation of the our system.

A study on the estimation of relative shift vector from aerial image sequence and aircraft attitude information (연속 항공영상과 비행체의 자세 정보를 이용한 상대적 편이 추정에 관한 연구)

  • 김종문;박래홍;이쾌희
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.147-152
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    • 1992
  • This paper describes a new approach that can extract the relative shift vectors between two aerial image sequences for implementing the visual navigation system. This method minimizes the noise included in the aircraft attitude information that represents the changes of the aircraft attitude using the statistical method and Kalman Filtering method. This result can be used to find the relative shift vectors which are independent of the attitude changes indicating the true trajectories of aircraft. We applied this method to the image about which we had already known the information of aircraft attitude, and that result showed that the errors were minimized successfully.

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Error Correction of Interested Points Tracking for Improving Registration Accuracy of Aerial Image Sequences (항공연속영상 등록 정확도 향상을 위한 특징점추적 오류검정)

  • Sukhee, Ochirbat;Yoo, Hwan-Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.2
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    • pp.93-97
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    • 2010
  • This paper presents the improved KLT(Kanade-Lucas-Tomasi) of registration of Image sequence captured by camera mounted on unmanned helicopter assuming without camera attitude information. It consists of following procedures for the proposed image registration. The initial interested points are detected by characteristic curve matching via dynamic programming which has been used for detecting and tracking corner points thorough image sequence. Outliers of tracked points are then removed by using Random Sample And Consensus(RANSAC) robust estimation and all remained corner points are classified as inliers by homography algorithm. The rectified images are then resampled by bilinear interpolation. Experiment shows that our method can make the suitable registration of image sequence with large motion.

Integrated Position Estimation Using the Aerial Image Sequence (항공영상을 이용한 통합된 위치 추정)

  • Sim, Dong-Gyu;Park, Rae-Hong;Kim, Rin-Chul;Lee, Sang-Uk
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.12
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    • pp.76-84
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    • 1999
  • This paper presents an integrated method for aircraft position estimation using sequential aerial images. The proposed integrated system for position estimation is composed of two parts: relative position estimation and absolute position estimation. Relative position estimation recursively computes the current position of an aircraft by accumulating relative displacement estimates extracted from two successive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameter estimates as an aircraft goes on navigating, resulting in large position error. Therefore absolute position estimation is required to compensate for the position error generated in relative position estimation. Absolute position estimation algorithms by image matching or digital elevation model (DEM) matching are presented. In image matching, a robust oriented Hausdorff measure (ROHM) is employed whereas in DEM matching an algorithm using multiple image pairs is used. Computer simulation with four real aerial image sequences shows the effectiveness of the proposed integrated position estimation algorithm.

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Speeding up the KLT Tracker for Realtime Image Georeferencing (실시간 영상 지오레퍼런싱을 위한 KLT 트랙커의 속도개선)

  • Supannee, Tanathong;Lee, Im-Pyeong
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2010.04a
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    • pp.77-80
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    • 2010
  • The demand for human security significantly promotes the development of surveillance applications using a multi-sensor integrated UAV system. For more sophisticated operations, the system should provide a sequence of images rectified in a ground coordinate system in realtime. This rectification requires accurate position and attitude of the camera at the time of exposure of each image, which can be estimated through an Aerial Triangulation process using the GPS/INS data and tie points between adjacent images. In this work, the KLT tracker is utilized to obtain the tie points. To satisfy the realtime requirements, we present an approach to speed up the tracker by supplying the initial guessed positions of tie points based on the exterior orientation. The experimental results show that, when the guessed positions are supplied, the KLT tracker consumed less computational time than the ordinary KLT which is more suitable to be incorporated into the realtime image georeferencing process.

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Real-Time Implementation of the Relative Position Estimation Algorithm Using the Aerial Image Sequence (항공영상에서 상대 위치 추정 알고리듬의 실시간 구현)

  • Park, Jae-Hong;Kim, Gwan-Seok;Kim, In-Cheol;Park, Rae-Hong;Lee, Sang-Uk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.3
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    • pp.66-77
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    • 2002
  • This paper deals with an implementation of the navigation parameter extraction technique using the TMS320C80 multimedia video processor (MVP). Especially, this Paper focuses on the relative position estimation algorithm which plays an important role in real-time operation of the overall system. Based on the relative position estimation algorithm using the images obtained at two locations, we develop a fast algorithm that can reduce large amount of computation time and fit into fixed-point processors. Then, the algorithm is reconfigured for parallel processing using the 4 parallel processors in the MVP. As a result, we shall demonstrate that the navigation parameter extraction system employing the MVP can operate at full-frame rate, satisfying real-time requirement of the overall system.

A Motion Detection Approach based on UAV Image Sequence

  • Cui, Hong-Xia;Wang, Ya-Qi;Zhang, FangFei;Li, TingTing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1224-1242
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    • 2018
  • Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

Vision-based full-field panorama generation by UAV using GPS data and feature points filtering

  • Guo, Yapeng;Xu, Yang;Niu, Haowei;Li, Zhonglong;E., Yuhui;Jiao, Xinghua;Li, Shunlong
    • Smart Structures and Systems
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    • v.25 no.5
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    • pp.631-641
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    • 2020
  • To meet the urgent requirements of safety surveillance from civil engineering management authorities, this study proposes a refined and efficient approach to generate full-field high-resolution panorama of construction sites using camera-amounted UAV (Unmanned Aerial Vehicle). GPS (Global Position System) information extraction for pre-registration, feature points filtering for efficient registration and optimal seaming line seeking for fusion are performed in sequence to form the full-field panorama generation framework. Advantages of the proposed method are as follows. First, GPS information can sort images for pre-registration, avoiding inefficient repeated pairwise calculations and matching. Second, the feature points are filtered according to the characteristics of the construction site images to reduce the amount of calculation. The proposed framework is validated on a road construction site and results demonstrate that it can generate an accurate and high-quality full-site panorama for the safety supervision in a much efficient manner.