• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.249-255
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• 2011

The free-stereo mosaics image without GPS/INS and ground control data can be generated by using relative orientation parameters on the 3D model coordinate system. Its origin is located in one reference frame image. A 3D coordinate calculated by conjugate points on the free-stereo mosaic images is represented on the 3D model coordinate system. For determining 3D coordinate on the 3D absolute coordinate system utilizing conjugate points on the free-stereo mosaic images, transformation methodology is required for transforming 3D model coordinate into 3D absolute coordinate. Generally, the 3D similarity transformation is used for transforming each other 3D coordinates. Error of 3D model coordinates used in the free-stereo mosaic images is non-linearly increased according to distance from 3D model coordinate and origin point. For this reason, 3D model coordinates used in the free-stereo mosaic images are difficult to transform into 3D absolute coordinates by using linear transformation. Therefore, methodology for transforming nonlinear 3D model coordinate into 3D absolute coordinate is needed. Also methodology for resampling the free-stereo mosaic image to the geo-stereo mosaic image is needed for overlapping digital map on absolute coordinate and stereo mosaic images. In this paper, we propose a 3D non-linear transformation for converting 3D model coordinate in the free-stereo mosaic image to 3D absolute coordinate, and a 2D non-linear transformation based on 3D non-linear transformation converting the free-stereo mosaic image to the geo-stereo mosaic image.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.182-187
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• 1999

Stereo matching is one of the most crucial parts in DEM generation. Naive stereo matching algorithms often create many holes and blunders in a DEM and therefore a carefully designed strategy must be employed to guide stereo matching algorithms to produce “good” 3D information. In this paper, we describe one such a strategy designed by the use of scene geometry, in particular, the epipolarity for generation of a DEM from linear pushbroom images. The epipolarity for perspective images is a well-known property, i.e., in a stereo image pair, a point in the reference image will map to a line in the search image uniquely defined by sensor models of the image pair. This concept has been utilized in stereo matching by applying epipolar resampling prior to matching. However, the epipolar matching for linear pushbroom images is rather complicated. It was found that the epipolarity can only be described by a Hyperbola- shaped curve and that epipolar resampling cannot be applied to linear pushbroom images. Instead, we have developed an algorithm of incorporating such epipolarity directly in least squares correlation matching. Experiments showed that this approach could improve the quality of a DEM.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.421-432
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• 2015

There are significant differences in geometric property and stereo model accuracy between single-sensor stereo that uses two images taken by stereo acquisition mechanism within identical sensor and dual-sensor stereo that randomly combines two images taken from two different sensors. This paper compares the two types of stereo pairs thoroughly. For experiment, two single-sensor stereo pairs and four dual-sensor stereo pairs were constituted using SPOT-5 stereo and KOMPSAT-2 stereo covering same area. While the two single-sensor stereos have stable geometry, the dual-sensor stereos produced two stable and two unstable geometries. In particular, the unstable geometry led to a decrease in stereo model accuracy of the dual-sensor stereos. The two types of stereo pairs were also compared under the stable geometry. Overall, single-sensor stereos performed better than dual-sensor stereos for vertical mapping, but dual-sensor stereos was more accurate for horizontal mapping. This paper has revealed the differences of two types of stereos with their geometric properties and positioning accuracies, suggesting important considerations for handling satellite stereo images, particularly for dual-satellite stereo images.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.04b
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• pp.42-44
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• 2002

The experimental model of the 8-view stereoscopic display system using the photopolymer-based VHOE is proposed. At first, the VHOE is implemented by angle-multiplexed recording of 8-view's diffraction gratings using the optimized exposure-time scheduling scheme in the photopolymer (HRF-150-100) and then. the VHOE-based 8-view stereoscopic display system is implemented by sequentially synchronizing the incident angles of the reference beam of the VHOE with the 8-view stereo images on the LCD pannel. Accordingly, from some experimental results using 8-view images generated by the toed-in stereo camera system, it is found that 8-view stereo images can be diffracted to eight different directions time-sequentially and there is some disparity between the stereo images.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.347-353
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• 2000

The purpose of this paper is to extract DEM (Digital Elevation Model) using KOMPSAT images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. Area based matching method is used to find the corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation information obtained from sensor modeling and the disparity from the stereo matching. In experiment, the KOMPSAT images, 2592$\times$2796 panchromatic images are used to extract DEM. The experiment result show the DEM using KOMPSAT images.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.212-222
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• 2003

The ability to efficiently and robustly recover accurate 3D terrain models from sets of stereoscopic images is important to many civilian and military applications. A stereo matching has been an important tool for reconstructing three dimensional terrain. However, there exist many factors causing stereo matching error, such as occlusion, no feature or repetitive pattern in the correlation window, intensity variation, etc. Among them, occlusion can be only resolved by true multi-image stereo. In this paper, we present multi-image stereo method using DEM fusion as one of efficient and reliable true multi-image methods. Elevations generated by all pairs of images are combined by the fusion process which accepts an accurate elevation and rejects an outlier. We propose three fusion schemes: THD(Thresholding), BPS(Best Pair Selection) and MS(Median Selection). THD averages elevations after rejecting outliers by thresholding, while BPS selects the most reliable elevation. To determine the reliability of a elevation or detect the outlier, we employ the measure of self-consistency. The last scheme, MS, selects the median value of elevations. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental results indicate that all three fusion schemes showed much better improvement over the conventional binocular stereo in natural terrain of 29 Palms and urban site of Avenches.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.36-40
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• 1996

There are two prevailing techniques, mechanical and optical profilometers, to measure 3-dimensional configurations of the human skin furrows. The methods have some limitations such as, accuracies or resolutions of the acquired 3-dimensional data and consistencies according to the repeated experiments. We devised an optical profilometer that is called stereo image optical profilometer (SOP) based on stereo image processing techniques. A stereo image is a pair of images that obtained from two cameras which have different angles. From the digital stereo images, the clinical informations for skin can be obtained by some signal processing techniques. In this paper, we focused on the 3-dimensional graphical visualizations of the structures and state of the skin furrows by solving the corresponding problem from the left and right pairs of the stereo images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.453-460
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• 2009

For constructing 3D information using aerial photograph or video sequences, left and right stereo images having different viewing angle should be prepared in overlapping area. In video sequences, left and right stereo images would be generated by mosaicing left and right slice images extracted in consecutive video sequences. Therefore, this paper is focused on generating left and right stereo mosaic images that are able to construct 3D information and video sequences could be made for the best use. In the stereo mosaic generation, motion parameters between video sequences should be firstly determined. In this paper, to determine motion parameters, free mosaic method using geometric relationship, such as relative orientation parameters, between consecutive frame images without GPS/INS geo-data have applied. After determining the motion parameters, the mosaic image have generated by 4 step processes: image registration, image slicing, determining on stitching line, and 3D image mosaicking. As the result of experiment, generated stereo mosaic image and analyzed result of x, y-parallax have showed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1431-1438
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• 1995

In this paper, we present a multiple-view stereo matching method in case of moving in the direction of optical axis with stereo camera. Also we analyze the obtainable depth precision to show that multiple-view stereo increases the virtual baseline with single-view stereo. This method decides candidate points for correspondence in each image pair and then search for the correct combinations of correspondences among them using the geometrical consistency they must satisfy. Adantages of this method are capability in increasing the accuracy in matching by using the multiple stereo images and less computation due to local processing. This method computes 3-D depth by averaging the depth obtained in each multiple-view stereo. We show that the resulting depth has more precision than depth obtainable by each independent stereo when the position of image feature is uncertain due to image noise. This paper first defines a multipleview stereo agorithm in case of moving in the direction of optical axis with stereo camera and analyze the obtainable precision of computed depth. Then we represent the effect of removing the incorrect matching candidate and precision enhancement with experimental result.