• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.58-65
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• 2009

The paper identifies noise characteristics of a nonliner image sensor model which reflects a saturation effect of each detector pixel and extends the result to estimate an image SNR (Signla-to-Noise Ratio) distribution over all the pixels in a detector. In particular, nonlinearity of a pixel is studied from two perspectives of including asymmetry of a noise PDF (Probability Distribution Function) and enhancing a pixel SNR value, in comparison to a linear model. It is noted that the proposed image SNR distribution function is useful to effectively select new optimal operation parameter values: an integration time and an pixel-summing number, even after a launch campaign, assuming sensor gain degradation in orbit or inevitable modification of some operation parameter values due to space contingency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.848-856
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• 2004

In this paper, a fast stereo matching algorithm based on pixel-wise matching strategy, which can get a stable and accurate disparity map, is proposed. Since a stereo image pair has small differences each other and the differences between left and right images are just caused by horizontal shifts with some order, the matching using a large window will not be needed within a given search range. However, disparity results of conventional pixel-based matching methods are somewhat unstable and wrinkled, the principal direction of disparities is checked by the accumulated cost along a path on array with the dynamic programming method. Experimental results showed that the proposed method could remove almost all disparity noise and set a good quality disparity map in very short time.

• Journal of Sensor Science and Technology
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• v.21 no.3
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• pp.211-216
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• 2012

Fires are the most common disaster and early fire detection is of great importance to minimize the consequent damage. Simple sensors including smoke detectors are widely used for the purpose but they are able to sense fires only at close proximity. Recently, due to the rapid advances of relevant technologies, vision-based fire sensing has attracted growing attention. In this paper, a novel visual sensing technique to automatically detect fire is presented. The proposed technique consists of multiple steps of image processing: pixel-level, block-level, and frame level. At the first step, fire flame pixel candidates are selected based on their color values in YIQ space from the image of a camera which is installed as a vision sensor at a fire scene. At the second step, the dynamic parts of flames are extracted by comparing two consecutive images. These parts are then represented in regularly divided image blocks to reduce pixel-level detection error and simplify following processing. Finally, the temporal change of the detected blocks is analyzed to confirm the spread of fire. The proposed technique was tested using real fire images and it worked quite reliably.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.721-724
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• 1998

A circular image in a space don't appear as an exact circular image and appear as an oval in image buffer because distortion of camera lens, number of horizontal pixel of CCD photographing element and unmber of horizontal pixel of image buffer are not in accordance. By using familiar 3-D coordinate, know as circle's diameter, and cicle's center, you correct a pin-hole camera and get an exact circle with reprojection a circle into image buffer, according to a perspective.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.42.2-43
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• 2021

We address a question of what are three main channels that can best translate other channels in ultraviolet (UV) and extreme UV (EUV) observations. For this, we compare the image translations among the nine channels of the Atmospheric Imaging Assembly on the Solar Dynamics Observatory using a deep learning model based on conditional generative adversarial networks. In this study, we develop 170 deep learning models: 72 models for single-channel input, 56 models for double-channel input, and 42 models for triple-channel input. All models have a single-channel output. Then we evaluate the model results by pixel-to-pixel correlation coefficients (CCs) within the solar disk. Major results from this study are as follows. First, the model with 131 Å shows the best performance (average CC = 0.84) among single-channel models. Second, the model with 131 and 1600 Å shows the best translation (average CC = 0.95) among double-channel models. Third, among the triple-channel models with the highest average CC (0.97), the model with 131, 1600, and 304 Å is suggested in that the minimum CC (0.96) is the highest. Interestingly they are representative coronal, photospheric, and chromospheric lines, respectively. Our results may be used as a secondary perspective in addition to primary scientific purposes in selecting a few channels of an UV/EUV imaging instrument for future solar satellite missions.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.43.1-43.1
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• 2019

In this study, we apply a deep learning model to denoising solar magnetograms. For this, we design a model based on conditional generative adversarial network, which is one of the deep learning algorithms, for the image-to-image translation from a single magnetogram to a denoised magnetogram. For the single magnetogram, we use SDO/HMI line-of-sight magnetograms at the center of solar disk. For the denoised magnetogram, we make 21-frame-stacked magnetograms at the center of solar disk considering solar rotation. We train a model using 7004 paris of the single and denoised magnetograms from 2013 January to 2013 October and test the model using 1432 pairs from 2013 November to 2013 December. Our results from this study are as follows. First, our model successfully denoise SDO/HMI magnetograms and the denoised magnetograms from our model are similar to the stacked magnetograms. Second, the average pixel-to-pixel correlation coefficient value between denoised magnetograms from our model and stacked magnetogrmas is larger than 0.93. Third, the average noise level of denoised magnetograms from our model is greatly reduced from 10.29 G to 3.89 G, and it is consistent with or smaller than that of stacked magnetograms 4.11 G. Our results can be applied to many scientific field in which the integration of many frames are used to improve the signal-to-noise ratio.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.23.1-23.1
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• 2011

The SMT is a subsystem of the UFFO (Ultra-Fast Flash Observatory) pathfinder onboard the Lomonosov spacecraft planed to be launched in November 2011. The UFFO is designed for extremely fast observation of optical afterglow of Gamma Ray Burst (GRB). This study is primarily concerned with performance measurement of the SMT optical system under the integration and test phase. SMT is a 100mm Ritchey-Chretien type telescope with a motorized slewing mirror and a $256{\times}256$ pixels Intensified Charge-Coupled Device (ICCD) of 22.2${\mu}m$ in pixel size. SMT is designed to operate over the wavelength coverage between 200 nm and 650 nm. It has 17 arcmin FOV (Field of View), providing 4arcsec in detector pixel resolution. In this study, we describe the integration and test process of the SMT optical system and interim performance measurement results with motorized slewing mirror and ICCD.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.29-35
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• 2012

In this paper, it is presented the method of image recovering which existing is only pixel processing, but suggesting method is concluding image clustering overlap degree after classfying around unit fixel to crowd pixel. Concluding overlap degree threshold value is after identifying pattern pixel and grasping geometry structure of sample pattern and deduction of deciding function. distinguishing feature space is above four dimension is reason of not visual observation of pattern structure. consideration of distribution structure is distance of center of crowd pixel, the number of each crowd pattern pixel and standard deviation. The over threshold value elimate the overlap image and the downward is recovered and established dynamic image. memory storage deduction of 20% and elevation of 15% performance is estimated in recovery of image.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.459-462
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• 2009

Hatching is an effective artistic tool for conveying shape and shading by placing parallel line strokes on drawing objects. We present a simple and effective per-pixel image-space hatching method to draw line strokes using given stroke directions. Our hatching method directly runs on the screen and it can efficiently render highly complex scenes in hatching styles. We implement the algorithm using a pixel shader in a modern GPU.

• Bulletin of the Korean Space Science Society
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• 2003.10a
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• pp.104-104
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• 2003

본 포스터에서는 다목적 위성 2호의 주 탑재체인 MSC(Multi-Spectral Camera)가 TDI(Time Delayed Integration) 방식을 채택함에 따라, TDI에 의해 MSC 영상 자료가 어떻게 영향을 받게 되는 지를 연구한 내용을 설명한다. MSC는 지상 해상도가 1m인 고해상도에서 영상을 촬영하기 때문에 상대적으로 입사 광량이 부족한 문제를 안고 있음에 따라 32 line의 TDI 방식을 사용한다. TDI 방식을 사용하여 MSC에서 직하방향으로 영상을 촬영할 경우, 영상의 가운데 pixel에서 멀어질수록 TDI에 의해 영상의 MTF 값이 떨어지는 결과가 발생한다. 또한, 다목적 위성 2호는 Roll 축을 중심으로 $\pm$30도 Pitch 축을 중심으로 $\pm$30도 tilt를 하여 영상을 촬영하도록 운영될 예정이기 때문에 더더욱 TDI에 의채 영상의 MTF 값이 떨어지는 결과가 발생하게 된다. 이외에도 TDI는 다목적 위성 2호의 고도가 감소하거나, Yaw 축의 변화, Jitter 등에 의해서도 영상의 MTF 값이 감소하게 된다. 물론 MSC CCD pixel의 sampling rate인 Line Rate 값을 각각의 경우에 따라 적절한 값을 부여함으로써 TDI에 의한 MTF 값의 감소를 많은 부분은 수습할 수 있으나 완벽한 보정은 힘든 상황이다.