• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.495-506
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• 2017

This study was carried out to effectively perform relative color correction for high-resolution aerial ortho image. For this study, relative geometrical error between adjacent images was analyzed. The block sum method is proposed to reduce the relative geometrical error. We used the regression coefficients determined based on the block sum size to perform the color correction. As a result, it was confirmed that the relative color correction was visually performed well. Quantitative analysis was performed through histogram similarity analysis. It is proved that block sum method is useful for relative color correction. Particularly, the block sum size was very important to correct color based on the amount of relative geometrical error.

• Proceedings of the Optical Society of Korea Conference
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• 1998.08a
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• pp.98-99
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• 1998

In this paper, an acousto-optic defiector9ADO) is used to perform the angular multiplexing without moving parts. The error-correction coding techniques was used to achive low bit-error rates in the experiment. A part of Lena image(64*64) encoded by Reed-Solomon codes were stored and retrieved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1923-1928
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• 2017

This paper is a study on error correction for three-dimensional shape reconstruction based on factorization method. The existing error correction method based on factorization has a limitation of correction because it is optimized globally. Thus in this paper, we propose our new method which can find and correct the only major error influence factor toward three-dimensional reconstructed shape instead of global approach. We define the error-influenced factor in two-dimensional re-projection deviation space and directly control the error components. In addition, it is possible to improve the error correcting performance by recursively applying the above process. This approach has an advantage under noise because it controls the major error components without depending on any geometric information. The performance evaluation of the proposed algorithm is verified by simulation with synthetic and real image sequence to demonstrate noise robustness.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.234-332
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• 2001

For a method improving fractal image segmentation which is a new application of fractal image coding, YST scheme have proposed an image segmentation scheme using labeling based on periodic points of pixel transformation and error-correction of labels by iterating fractal transformation. The scheme generates the high quality segmentation, however, it has the redundancy in the process of labeling and correction of labels. To solve this problem, we propose a labeling algorithm based on orbit of pixel transformation and restricted condition on iterating process of fractal transformation.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.137-148
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• 1998

An algorithm developed for the precision correction of high resolution satellite images is introduced in this paper. In general, the polynomial warping algorithm which derives polynomial equations between GCPs extracted from an image and a base map requires many GCPs well-distributed over the image. The precision correction algorithm described in this paper is based on a sensor-orbit-Earth geometry, and therefore, it is capable of correcting a raw image using only 2-3 GCPs. This algorithm estimates the errors on the orbit determination and the attitude of the satellite by using a Kalman filter. This algorithm was implemented, tested and integrated into the KITSAT-3 image preprocessing software.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.745-751
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• 2013

In naval gun firing, firing accuracy comes from the combination of each component's accuracy in CFCS (Command and Fire Control System) like tracking sensors and gun. Generally, battery alignment is done to correct the error between gun and tracking sensor by using boresight telescope on harbor and sea. But normally, the battery alignment can compensate only the static alignment error and ignore dynamic alignment error which is caused by own ship movement. There was no research on this dynamic alignment error until now. We propose a new way to analyze dynamic arrangement error by using image of boresight telescope. In case of the dynamic alignment error was due to time delay of own ship attitude information, we propose the way to compensate it.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.153-166
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• 2020

DDI(Display Driver IC) are used to drive numerous pixels that make up display. For stable driving of DDI, it is necessary to attach a protective film to shield electromagnetic waves. When the protective film is attached, defects often occur if the film is inclined or the center point is not aligned. In order to minimize such defects, an algorithm for correcting the center point and the inclined angle using camera image information is required. This technology detects the corner coordinates of the protective film by image processing in order to correct the positional defects where the protective film is attached. Corner point coordinates are detected using an algorithm, and center point position finds and correction values are calculated using the detected coordinates. LUT (Lookup Table) is used to quickly find out whether the angle is inclined or not. These algorithms were described by Verilog HDL. The method using the existing software requires a memory to store the entire image after processing one image. Since the method proposed in this paper is a method of scanning by adding a line buffer in one scan, it is possible to scan even if only a part of the image is saved after processing one image. Compared to those written in software language, the execution time is shortened, the speed is very fast, and the error is relatively small.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.605-606
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• 2005

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.109-114
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.