• Title/Summary/Keyword: parallel projection model

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DIRECT EPIPOLAR IMAGE GENERATION FROM IKONOS STEREO IMAGERY BASED ON RPC AND PARALLEL PROJECTION MODEL

  • Oh, Jae-Hong;Kim, Kyung-Ok
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.860-863
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    • 2006
  • Epipolar images have to be generated to stereo display aerial images or satellite images. Pushbroom sensor is used to acquire high resolution satellite images. These satellite images have curvilinear epipolar lines unlike the epipolar lines of frame images, which are straight lines. The aforementioned fact makes it difficult to generate epipolar images for pushbroom satellite images. If we assume a linear transition of the sensor having constant speed and attitude during image acquisition, we can generate epipolar images based on parallel projection model (2D Affine model). Recent high resolution images are provided with RPC values so that we can exploit these values to generate epipolar images without using ground control points and tie point. This paper provides a procedure based on the parallel projection model for generating epipolar images directly from a stereo IKONOS images, and experimental results.

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Direct Epipolar Image Generation From IKONOS Stereo Imagery Based On RPC and Parallel Projection Model

  • Oh, Jae-Hong;Shin, Sung-Woong;Kim, Kyung-Ok
    • Korean Journal of Remote Sensing
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    • v.22 no.5
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    • pp.451-456
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    • 2006
  • Epipolar images have to be generated to stereo display aerial images or satellite images. Pushbroom sensor is used to acquire high resolution satellite images. These satellite images have curvilinear epipolar lines unlike the epipolar lines of frame images, which are straight lines. The aforementioned fact makes it difficult to generate epipolar images for pushbroom satellite images. If we assume a linear transition of the sensor having constant speed and attitude during image acquisition, we can generate epipolar images based on parallel projection model (20 Affine model). Recent high resolution images are provided with RPC values so that we can exploit these values to generate epipolar images without using ground control points and tie point. This paper provides a procedure based on the parallel projection model for generating epipolar images directly from a stereo IKONOS images, and experimental results.

3D Surface Model Generation of Micro Structure by Self Calibration of The SEM Image (SEM 영상의 자체검정에 의한 미세구조물의 3차원 표면모델 생성)

  • 이효성;박형동
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.04a
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    • pp.151-159
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    • 2003
  • This study presents method for self-calibration of the SEM(Scanning Electron Microscope) stereo image using the standard microprobe with same grid pattern and using parallel and central perspective projection equation. Result showed that parallel projection method is more suitable for standard microprobe. The maximum error of 3D coordinates acquired by this method did not exceed 5 $\mu\textrm{m}$, and DSM(Digital Surface Model) for three dimensional measurement of the rock sample was generated by the digital photogrammetry. This result can be used for quantification of micro scale change of shape and analysis of the micro morphology of rock due to weathering.

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Epipolar Resampling for High Resolution Satellite Imagery Based on Parallel Projection (평행투영 기반의 고해상도 위성영상 에피폴라 재배열)

  • Noh, Myoung-Jong;Cho, Woo-Sug;Chang, Hwi-Jeong;Jeong, Ji-Yeon
    • Journal of Korean Society for Geospatial Information Science
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    • v.15 no.4
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    • pp.81-88
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    • 2007
  • The geometry of satellite image captured by linear CCD sensor is different from that of frame camera image. The fact that the exterior orientation parameters for satellite image with linear CCD sensor varies from scan line by scan line, causes the difference of image geometry between frame and linear CCD sensor. Therefore, we need the epipolar geometry for linear CCD image which differs from that of frame camera image. In this paper, we proposed a method of resampling linear CCD satellite image in epipolar geometry under the assumption that image is not formed in perspective projection but in parallel projection, and the sensor model is a 2D affine sensor model based on parallel projection. For the experiment, IKONOS stereo images, which are high resolution linear CCD images, were used and tested. As results, the spatial accuracy of 2D affine sensor model is investigated and the accuracy of epipolar resampled image with RFM was presented.

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Locally Initiating Line-Based Object Association in Large Scale Multiple Cameras Environment

  • Cho, Shung-Han;Nam, Yun-Young;Hong, Sang-Jin;Cho, We-Duke
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.3
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    • pp.358-379
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    • 2010
  • Multiple object association is an important capability in visual surveillance system with multiple cameras. In this paper, we introduce locally initiating line-based object association with the parallel projection camera model, which can be applicable to the situation without the common (ground) plane. The parallel projection camera model supports the camera movement (i.e. panning, tilting and zooming) by using the simple table based compensation for non-ideal camera parameters. We propose the threshold distance based homographic line generation algorithm. This takes account of uncertain parameters such as transformation error, height uncertainty of objects and synchronization issue between cameras. Thus, the proposed algorithm associates multiple objects on demand in the surveillance system where the camera movement dynamically changes. We verify the proposed method with actual image frames. Finally, we discuss the strategy to improve the association performance by using the temporal and spatial redundancy.

DEM Generation from IKONOS Imagery by Using Parallel Projection Model (평행투영모형에 의한 IKONOS 위성영상의 수치고도모형 생성)

  • Kim, Eui-Myoung;Kim, Seong-Sam;Yoo, Hwan-Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.1 s.31
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    • pp.55-61
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    • 2005
  • Digital Elevation Model (DEM) generation from remotely sensed imagery is crucial for a variety of mapping applications such as ortho-photo generation, city modeling. High resolution imaging satellites such as SPOT-5, IKONOS, QUICK-BIRD, ORBVIEW constitute an excellent source for efficient and economic generation of DEM data. However, prerequisite knowledge in the areas of sensor modeling, epipolar resampling, and image matching is required to generate DEM from these high resolution satellite imagery. From the above requirements, epipolar resampling emerges as the most important factors. Research attempts in this area are still in high demand and short supply. Another cause that adds to the complication of the problem is that most studies of DEM generation from IKONOS scenes have been based on rational function model. In this paper, we proposed a new methodology for DEM generation from satellite scenes using parallel projection model which is sensor independent, makes it possible for sensor modeling and epipolar resampling by only few control points. The performance and feasibility of the developed methodology is evaluated through real dataset captured by IKONOS.

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An improvement of estimators for the multinormal mean vector with the known norm

  • Kim, Jaehyun;Baek, Hoh Yoo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.435-442
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    • 2017
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}$ (p ${\geq}$ 3) under the quadratic loss from multi-variate normal population. We find a James-Stein type estimator which shrinks towards the projection vectors when the underlying distribution is that of a variance mixture of normals. In this case, the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is known where K is a projection vector with rank(K) = q. The class of this type estimator is quite general to include the class of the estimators proposed by Merchand and Giri (1993). We can derive the class and obtain the optimal type estimator. Also, this research can be applied to the simple and multiple regression model in the case of rank(K) ${\geq}2$.

Parallel Model Feature Extraction to Improve Performance of a BCI System (BCI 시스템의 성능 개선을 위한 병렬 모델 특징 추출)

  • Chum, Pharino;Park, Seung-Min;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.11
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    • pp.1022-1028
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    • 2013
  • It is well knowns that based on the CSP (Common Spatial Pattern) algorithm, the linear projection of an EEG (Electroencephalography) signal can be made to spaces that optimize the discriminant between two patterns. Sharing disadvantages from linear time invariant systems, CSP suffers from the non-stationary nature of EEGs causing the performance of the classification in a BCI (Brain-Computer Interface) system to drop significantly when comparing the training data and test data. The author has suggested a simple idea based on the parallel model of CSP filters to improve the performance of BCI systems. The model was tested with a simple CSP algorithm (without any elaborate regularizing methods) and a perceptron learning algorithm as a classifier to determine the improvement of the system. The simulation showed that the parallel model could improve classification performance by over 10% compared to conventional CSP methods.

An Image modification algorithm under the convergence camera model (수렴 카메라 모델에서의 영상 수정 알고리즘)

  • 유용현;송원석;이정안;김민기
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.373-376
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    • 2003
  • This paper presents a image modification algorithm using the convergence camera model and the two perspective projection matrixes of the original cameras. Any pair of images can be transformed se that epipolar lines are parallel and horizontal in each image. The advantage of modification is that a 2-D search problem is reduced to a 1-D search problem. Reconstruction can be performed directly from the rectified images.

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Comparison Among Sensor Modeling Methods in High-Resolution Satellite Imagery (고해상도 위성영상의 센서모형과 방법 비교)

  • Kim, Eui Myoung;Lee, Suk Kun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6D
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    • pp.1025-1032
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    • 2006
  • Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.