• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.89-97
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• 2013

Recently, economic and social damages are globally increased due to the heavy snowfall caused by global warming. To reduce the damages of sudden regional heavy snow in roads, suitable countermeasures should be established based on the accurate detection of snowfall intensity for each roadway segment. In this paper, we deal with snowfall intensity detecting algorithm in the road area from CCD Imagery. First, we determine the MLZ (MotionLess Zone), which does not contain lane markings and moving cars, in the image space. Next, snow streaks trespassing the MLZ are extracted with Canny operator and proposed algorithm. Also, the concept of SII (Snow Intensity Index), which is the number of snow streaks during one minute in the MLZ, is defined. Finally, the effectiveness of proposed algorithm is proved by visually comparing the imagery and SII value obtained during 69 minutes. In consequence, we figured out that the integration of SII is significantly related to an actual amount of snowfall.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.177.1-177
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• 2001

This paper describes the design of a NUC(Non-uniformity Correction) module in MSC(Multispectral Camera) which will be a payload on KOMPSAT. This module is required inside a system with data compression module like MSC to minimize the loss of imagery due to non-uniform characteristics between CCD pixels when the imagery is received and processed on a ground station. It comprises Hotlink input/output for imagery data, RS-422 interface with main controller in MSC, a number of SRAMS for storing imagery data and parameters, FPGA controllers which control the entire NUC module under the control of main controller, etc. It inputs 8-channel imagery pixel data which consist of 2-channel MS(Multispectral) band and ...

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.53-56
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• 2010

An aerial multi-looking camera system equips itself with five separate cameras which enables acquiring one vertical image and four oblique images at the same time. This provides diverse information about the site compared to aerial photographs vertically. However, multi-looking Aerial Camera for building a 3D spatial information don't use a large-size CCD camera, do uses a medium-size CCD camera, if acquiring forward, backward, left and right imagery of Certain objects, Aerial photographing set overlap and sidelap must be considered. Especially, Sideward-looking camera set up by the sidelap to determine whether a particular object can be acquisition Through our research we analyzed of sideward footprint and aerial photographing efficiency of Multi-view imagery by sidelap changing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.41-50
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• 1998

The object positional data in the form of digital imagery is processed and stored and is updated easily. The GPS, positioning system using satellites, is acquired its utilities in many parts because it is very easy to get the three dimensional coordinates using GPS around the world. For the effective acquisition of positional data to-ward objects in space, the automation of digital photogrammetry must be done and data acquisition and processing should be performed in real-time. In this study, the program is developed for automatic process of digital photogrammetry and the VAN that has CCD cameras and GPS receivers onboard is built for mobile positioning system. Also, the three dimensional positioning toward 20 objects which are vertical to the ground is done using left and right imagery of CCD cameras and GPS. For a base research in real-time photogrammetry, the three dimensional positioning is performed using continuous imagery and GPS and the three dimensional positioning accuracy is analyzed.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.504-507
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• 2007

The KOMPSAT-2 satellite is a push-broom system with MSC (Multi Spectral Camera) which contains a panchromatic band and four multi-spectral bands covering the spectral range from 450nm to 900nm. The PAN band is composed of six CCD array with 2528 pixels. And the MS band has one CCD array with 3792 pixels. Raw imagery generated from a push-broom sensor contains vertical streaks caused by variability in detector response, variability in lens falloff, pixel area, output amplifiers and especially electrical gain and offset. Relative radiometric calibration is necessary to account for the detector-to-detector non-uniformity in this raw imagery. Non-uniformity correction (NUC) is that the process of performing on-board relative correction of gain and offset for each pixel to improve data compressibility and to reduce banding and streaking from aggregation or re-sampling in the imagery. A relative gain and offset are calculated for each detector using scenes from uniform target area such as a large desert, forest, sea. In the NUC of KOMPSAT-2, The NUC table for each pixel are divided as HF NUC (high frequency NUC) and LF NUC (low frequency NUC) to apply to few restricted facts in the operating system ofKOMPSAT-2. This work presents the algorithm and process of NUC table generation and shows the imagery to compare with and without calibration.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.233-238
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• 2004

This study deals with the extraction of highway's superelevation using digital imagery which are economic method in constructing database for the side of highway management. Using CCD camera, both center line and shoulder of highway are measured by analyzing the result value and enough result values were obtained. This study is expected to become effective method for extraction of highway alignment elements in the Digital Photogrammetry.

• 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.

• Aerospace Engineering and Technology
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• v.6 no.1
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• pp.209-212
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• 2007

In the NUC of KOMPSAT-2, The NUC table for each pixel are divided as HF NUC(high frequency NUC) and LF NUC (low frequency NUC) to apply to few restricted facts in the operating system of KOMPSAT-2. This work presents the algorithm and process of NUC table generation and shows the imagery to compare with and without calibration.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.220-223
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• 2008

A camera system for the satellite application performs the mission of observation by measuring radiated light energy from the target on the earth. As a development stage of the system, the signal level analysis by estimating the number of electron collected in a pixel of an applied CCD is a basic tool for the performance analysis like SNR as well as the data path design of focal plane electronic. In this paper, two methods are presented for the calculation of the number of electrons for signal level analysis. One method is a quantitative assessment based on the CCD characteristics and design parameters of optical module of the system itself in which optical module works for concentrating the light energy onto the focal plane where CCD is located to convert light energy into electrical signal. The other method compares the design\ parameters of the system such as quantum efficiency, focal length and the aperture size of the optics in comparison with existing camera system in orbit. By this way, relative count of electrons to the existing camera system is estimated. The number of electrons, as signal level of the camera system, calculated by described methods is used to design input circuits of AD converter for interfacing the image signal coming from the CCD module in the focal plane electronics. This number is also used for the analysis of the signal level of the CCD output which is critical parameter to design data path between CCD and A/D converter. The FPE(Focal Plane Electronics) designer should decide whether the dividing-circuit is necessary or not between them from the analysis. If it is necessary, the optimized dividing factor of the level should be implemented. This paper describes the analysis of the electron count of a camera system for a satellite application and then of the signal level for the interface design between CCD and A/D converter using two methods. One is a quantitative assessment based on the design parameters of the camera system, the other method compares the design parameters in comparison with those of the existing camera system in orbit for relative counting of the electrons and the signal level estimation. Chapter 2 describes the radiometry of the camera system of a satellite application to show equations for electron counting, Chapter 3 describes a camera system briefly to explain the data flow of imagery information from CCD and Chapter 4 explains the two methods for the analysis of the number of electrons and the signal level. Then conclusion is made in chapter 5.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.9-15
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• 2011

Since PAN(panchromatic) and MS(multispectral) imagery of pushbroom scanner have the offset between PAN and MS CCD(charge coupled device) in the focal plane, PAN and MS images are acquired at different time and angle. Since clouds are fast moving objects, they should lead mis-registration problem with wrong matching points on clouds. The registration of cloudy imagery to recognize and remove the contamination of clouds can be categorized into three classes: (1) cloud is considered as nose and removed (2) employing multi-spectral imagery (3) using multi-temporal imagery. In this paper, method (1) and (3) are implemented and analysed with cloudy pushbroom scanner images.