• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.171-179
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• 2002

Sampling rates become inconsistent when spatial data in the spherical coordinate are resampled with respect to latitudinal or longitudinal degree for mathematical processes such as Fourier Transform, and this results in distortions of the processed data in the wavenumber domain. These distortions are more evident in the polar regions. An example is presented to show such distortions during the recovery process of free-air gravity anomalies from ERS-1 satellite radar altimeter data from the Barents Sea in the Russian Arctic, and a method is presented to minimize the distortion using the Lambert Conformal Conic map projection. This approach was found to enhance the free-air gravity anomalies in both data and wavenumber domains.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.868-876
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• 2021

Deploying deep neural network model training performs remarkable performance in the fields of Object detection and Instance segmentation. To train these models, features are first extracted from the input image using a backbone network. The extracted features can be reused by various tasks. Research has been actively conducted to serve various tasks by using these learned features. In this process, standardization discussions about encoding, decoding, and transmission methods are proceeding actively. In this scenario, it is necessary to analyze the response characteristics of features against various distortions that may occur in the data transmission or data compression process. In this paper, experiment was conducted to inject various distortions into the feature in the object recognition task. And analyze the mAP (mean Average Precision) metric between the predicted value output from the neural network and the target value as the intensity of various distortions was increased. Experiments have shown that features are more robust to distortion than images. And this points out that using the feature as transmission means can prevent the loss of information against the various distortions during data transmission and compression process.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.891-902
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• 2012

Reversible data hiding scheme is a form of steganography in which the secret embedding data can be retrieved from a stego image for the purpose of identification, copyright protection and making a covert channel. The reversible data hiding should satisfy that not only are the distortions due to artifacts against the cover image invisible but also it has large embedding capacity as far as possible. In this paper, we propose a robust reversible data hiding scheme by exploiting the differences between a center pixel and its neighboring pixels in each sub-block of the image to embed secret data into extra space. Moreover, our scheme enhances the embedding capacity and can recover the embedded data from the stego image without causing any perceptible distortions to the cover image. Simulation results show that our proposed scheme has lower visible distortions in the stego image and provides robustness to geometrical image manipulations, such as rotation and cropping operations.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.785-792
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• 2023

Because hyperspectral imaging provides detailed spectral information across a broad range of wavelengths, it can be utilized in numerous applications, including environmental monitoring, food quality inspection, medical diagnosis, material identification, art authentication, and crime scene analysis. However, hyperspectral images often contain various types of distortions due to the environmental conditions during image acquisition, which necessitates the proper removal of these distortions through a data preprocessing process. In this study, a preprocessing method was investigated to effectively correct the distortion caused by artificial light sources used in indoor hyperspectral imaging. For this purpose, a halogen-tungsten artificial light source was installed indoors, and hyperspectral images were acquired. The acquired images were then corrected for distortion using a preprocessing that does not require complex auxiliary equipment. After the corrections were made, the results were analyzed. According to the analysis, a statistical transformation technique using mean and standard deviation with reference to a reference signal was found to be the most effective in correcting distortions caused by artificial light sources.

• Proceedings of the KSEEG Conference
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• 2000.04b
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• pp.308-310
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• 2000

Sampling rates become inconsistent when spatial data in spherical coordinate are re-sampled with respect latitudinal or longitudinal degree for mathematical processes such as Fourier Transfrom, and this results in the distrtions of the processed data in the wavenmber domain. This distortions are more evident in the polar regions. An example is presented to show such distortions during the recovery process of free-air gravity anomalies from ERSI radar atimeter data in Russian Arctic Barents Sea, and a method is present to minimize the distortion using Lambect Conformal Conic map projection.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.267-277
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• 2019

Photogrammetry and computer vision are identical in determining the three-dimensional coordinates of images taken with a camera, but the two fields are not directly compatible with each other due to differences in camera lens distortion modeling methods and camera coordinate systems. In general, data processing of drone images is performed by bundle block adjustments using computer vision-based software, and then the plotting of the image is performed by photogrammetry-based software for mapping. In this case, we are faced with the problem of converting the model of camera lens distortions into the formula used in photogrammetry. Therefore, this study described the differences between the coordinate systems and lens distortion models used in photogrammetry and computer vision, and proposed a methodology for converting them. In order to verify the conversion formula of the camera lens distortion models, first, lens distortions were added to the virtual coordinates without lens distortions by using the computer vision-based lens distortion models. Then, the distortion coefficients were determined using photogrammetry-based lens distortion models, and the lens distortions were removed from the photo coordinates and compared with the virtual coordinates without the original distortions. The results showed that the root mean square distance was good within 0.5 pixels. In addition, epipolar images were generated to determine the accuracy by applying lens distortion coefficients for photogrammetry. The calculated root mean square error of y-parallax was found to be within 0.3 pixels.

• The Journal of Economics, Marketing and Management
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• v.3 no.2
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• pp.1-8
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• 2015

In this paper, the effects of auditor change on audit quality in companies accepted in Tehran stock exchange placed review and we assessed the presence or absence of a significant correlation between them. to assess the quality of data auditing and tax distortions, falsification of accounting estimates, distortion of rules, distortion caused by mistakes in applying accounting policies and other distortions are used as the dependent variable Is. the sample group consisted of 56 companies as experimental group and a control group of 56 other companies a 4-year period, during the years 2011 to 2014 were studied. data needed for research discovery success ratio distortion before and after the change of auditor. To test the research hypotheses paired comparison method is used.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.257-264
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• 1999

The lens distortions were corrected directly using the high-order polynomial which was offered in camera calibration data for the forward transformation and the root of Newton-Raphson's $2\times{2}$ nonlinear system for the backward transformation. The 0.04~0.08 pixels increase in accuracy was indicated through the use of direct correction of lens distortions instead of least square methods of commercial software. The least square adjustment method of high-order polynomial requires many control points which has a same weight. But this suggested method which is unnecessary to determine control points was developed and applied. The algorithm showed improved efficacy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.113-122
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• 2021

This study aims to investigate the effects of fiscal policy instruments on economic growth in Jordan using annual data from 1970 to 2019, by applying the VAR model (Vector Auto regression) and the Vector Error Correction Model (VECM). The study also examines the dynamic relationship among economic variables over time using the Granger casualty test, Impulse Response Function, and Variance Decomposition. The results show that not only the public expenditures have a positive effect on economic growth in Jordan, but also the tax revenues positively affect the economic growth in the short-run, and this is because of using the tax revenues to finance the government activities in Jordan. This effect becomes negative in the long run, and this is explained because the tax seems a source of distortions in the economy, The extreme taxes may cause huge distortions in the economy, and these distortions destroys the purchasing power, the aggregate demand, and supply. More governmental dependence on tax revenues is the main source of tax evasion and less efficiency. The effect of taxation will curb any prosperity in the economy. Therefore, the government should estimate the fair tax rates to generate sufficient revenues to finance the public expenditure required to enhance economic prosperity.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.181-197
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• 1996

Thc CCD earth image experiment(CEIE) is one of the main payload of the KITSAT-1. Since it was launched on Age. 11, 1992, the CEIE has taken more than 500 images on the earth surface world-wide so far. An image from the space is very different from a feature on the real Earth surface due to various radiometric and geometric distortions. Preprocessing to remove those distortions has to take place before the image data are processed and analyzed further for various applications. This paper summarizes the result of the operation of the CEIE and describes the procedure to perform preprocessing including radiometric and geometric correction.