• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.487-497
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• 2013

In this paper, a method of using high resolution stereo images is proposed to efficiently detect DSM errors. Automatically generated DSMs from stereo matching can be a useful solution to acquire DSM data in various aspects but they may include many gross errors coming from automatic processing. Therefore, a method to detect the gross errors on DSM is required for efficient DSM update. In this paper, stereo analysis using high resolution stereo images was investigated to represent reliability of DSM grids. The analysis enabled automatic detection of the gross errors which greatly influenced DSM quality. We used the reference DSM to assess reliability of our proposed method. We confirmed from experimental results that our method can be a valuable DSM errors analysis for efficient DSM correction. Our method is useful to analyze and improve DSM accuracy for various types of DSM and DEM. It is expected that our approach can be exploited for achievement of reliable DSM and DEM.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.939-948
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• 2020

CAS500-1 and CAS500-2 are high-resolution Earth-observing satellites being developed and scheduled to launch for land monitoring of Korea. The satellite information will be used for land usage analysis, change detection, 3D topological monitoring, and so on. Satellite image data of region of interests must be acquired in the stereo mode from different positions for 3D information generation. Accurate 3D processing and 3D display of stereo satellite data requires the epipolar image resampling process considering the pushbroom sensor and the satellite trajectory. This study developed an epipolar image resampling module for CAS-500 stereo data processing and verified its accuracy performance by testing along-track, across-track, and heterogeneous stereo data.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.273-285
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• 2007

Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.135-143
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• 2005

RPC(Rational Polynomial Camera) models have become the replacement model of choice for a number of high resolution satellite imagery providers. RPCs(Rational Polynomial Coefficients) provide a compact accurate representation of the ground to image geometry, allowing users to perform full photogrammetric processing of satellite imagery including block adjustment, 3D feature extraction and orthorectification. This paper presents an algorithm for 3D feature extraction using downhill simpler method which requires only function evaluations, not derivatives. The algorithm was implemented as an executable software program and tested using stereo IKONOS images of Seoul city. The results showed that the proposed algorithm was fast and accurate enough to be used as a practical method for the 3D feature extraction from stereo images with RPCs.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.61-70
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• 1995

In this paper, the algorithm to extract the height of flat-rooftop structures in stereo aerial image is suggested with an assumption that location, orientation, focal length, and field of view of a camera are known. It can be adapted to stereo aerial or satellite images. For performing feature-based stereo matching, the line segments suitable to describe the shape of general buildings are chosen as the feature. This paper is composed of three categories;the first step is to extract edges of structures with the polygon extraction algorithm which utilizes the edge following method, the second step is to perform the line segment matching with the camera information, and the last step is to calculate the location of each matched line and to estimate heights. The stereo images used in experiments are not real but synthetic ones. The experiment shows good results.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.471-482
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• 2019

The mission of the high-resolution camera for the lunar exploration is to provide 3D topographic information. It enables us to find the appropriate landing site or to control accurate landing by the short distance stereo image in real-time. In this paper, the ground verification and analysis system using the multi-application stereo camera to develop the high-resolution camera for the lunar exploration are proposed. The mission test items and test plans for the mission requirement are provided and the test results are analyzed by the ground verification and analysis system. For the realistic simulation for the lunar orbiter, the target area that has similar characteristics with the real lunar surface is chosen and the aircraft flight is planned to take image of the area. The DEM is extracted from the stereo image and compose three dimensional results. The high-resolution camera mission requirements for the lunar exploration are verified and the ground data analysis system is developed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1920-1925
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• 2004

This paper describes a new method for 3D object recognition which used surface segment-based stereo vision. The position and orientation of an objects is identified accurately enabling a robot to pick up, even though the objects are multiple and partially occluded. The stereo vision is used to get the 3D information as 3D sensing, and CAD model with its post processing is used for building models. Matching is initially performed using the model and object features, and calculate roughly the object's position and orientation. Though the fine adjustment step, the accuracy of the position and orientation are improved.

• 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.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.763-764
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• 2008

Sensing is an important part of a smart home system. Vision sensors are a type of passive systems, which are not sensitive to noise. In this paper, we implement a prototype for stereo vision systems using OpenCV. It is an open source library for computer vision developed by Intel corporation. The prototype will by used for comparing performance among various stereo algorithms and for developing a stereo vision smart camera.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.128.6-128
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• 2001

In this paper, we present a methodology of sensing and control for a robot system designed to be capable of grasping an object and moving it to target point Stereo vision system is employed to determine to depth map which represents the distance from the camera. In stereo vision system we have used a center-referenced projection to represent the discrete match space for stereo correspondence. This center-referenced disparity space contains new occlusion points in addition to the match points which we exploit to create a concise representation of correspondence an occlusion. And from the depth map we find the target object´s pose and position in 3-D space. To find the target object´s pose and position, we use the method of the model-based recognition.