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Moon, Byeongho,Yu, Soohwan,Ko, Seungyong,Park, Seonhee,Paik, Joonki Optical Society of America 2017 Journal of the Optical Society of America A Vol.34 No.6
<P>This paper presents a digital zooming method using a super-resolution (SR) algorithm based on the local self-similarity between the wide-and tele-view images acquired by an asymmetric dual camera system. The proposed SR algorithm consists of four steps: (i) registration of an optically zoomed image to the wide-view image, (ii) restoration of the central region of the zoomed wide-view image, (iii) restoration of the boundary region of the zoomed wideview image, and (iv) fusion of the results from steps (ii) and (iii). Since an asymmetric dual camera system acquires different-resolution images on the same scene due to the different optical specifications, the proposed method can restore the low-resolution wide-view image using the ideal high-frequency component estimated from the optically zoomed image. Experimental results demonstrate that the proposed method can provide significantly improved high-resolution wide-view images compared to existing single-image- based SR methods. (C) 2017 Optical Society of America</P>
Yeon, Sanghun,Yu, Byeongho,Seo, Byeongmo,Yoon, Yeobeom,Lee, Kwang Ho Elsevier 2019 SOLAR ENERGY -PHOENIX ARIZONA THEN NEW YORK- Vol.180 No.-
<P><B>Abstract</B></P> <P>Windows are the only part of a building that can directly penetrate the solar radiation into the occupied space and thus the shading devices are needed to control the solar penetration. A variety of research have been conducted to develop the optimized slat angle control in the existing literature, but the research incorporating artificial intelligence technique with slat angle control is limited thus far. Therefore, in this study, the ANN (Artificial Neural Network) model was applied to minimize the combined total load consisting of lighting, cooling, and heating loads through automatic slat angle control of venetian blinds. A three-story rectangular office building was simulated using EnergyPlus, and dimming control was applied to control the lighting. The interlocked simulation between Matlab and EnergyPlus was conducted through BCVTB. As a result of comparing automatic blind control via the ANN to fixed blind slat angle, the automatic blind control via the ANN showed 9.1% lower total load than the blind angle fixed at 50°. It was confirmed that the cooling and heating load could be significantly reduced by real-time automatic control via the ANN under various operating conditions, rather than fixing the blinds at one angle.</P> <P><B>Highlights</B></P> <P> <UL> <LI> ANN based slat angle control did not cause discomfort glare. </LI> <LI> Optimally controlled blind slat angle using ANN showed slightly higher lighting load than the fixed slat angle cases. </LI> <LI> As a result of the real-time optimal control of blind slat angle through the ANN, the reduction effect of the cooling load was found to be significant. </LI> <LI> When the blind slat angle was optimally controlled through the ANN, the total load reduction effect was shown to be remarkably excellent. </LI> </UL> </P>
Development of Cleaning Module for Wall Climbing Drone with Bio-inspired Watering Mechanism
Taewan Kim,Byeongho Yu,Christian Tirtawardhana,I Made Aswin Nahrendra,Hyun Myung 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
For many years, there has been significant progress in cleaning facilities in hazardous conditions using autonomous mechanical systems to keep humans away from potential danger. Especially, the cleaning method using a UAV (Unmanned Aerial Vehicle) has attracted much interest in the robotics field due to its high degree of freedom in maneuverability; however, a UAV has a payload limitation. In this paper, we propose a cleaning module for a specific drone platform “CAROS-Q” that can tilt its pose to perch on walls or tilted surfaces. The proposed module includes bio-inspired water flow control mechanism from the peristaltic movement of the Esophagus for improving cleaning performance while minimizing the complexity and weight. By comparing the cleaning performance between the proposed module and dry brush cleaning, it was confirmed that the proposed module outperforms the counterpart for cleaning various contaminants.
Low-light image restoration using bright channel prior-based variational Retinex model
Park, Seonhee,Moon, Byeongho,Ko, Seungyong,Yu, Soohwan,Paik, Joonki Springer (Biomed Central Ltd.) 2017 EURASIP journal on image and video processing Vol.2017 No.-
<P>This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization. The proposed method first estimates the bright channel to control the amount of brightness enhancement. Next, the variational Retinex-based energy function is iteratively minimized to estimate the improved illumination and reflectance using the BCP. Contrast of the estimated illumination is enhanced using the gamma correction and histogram equalization to reduce a color distortion and noise amplification. Experimental results show that the proposed method can provide the better restored result than the existing methods without unnatural artifacts such as noise amplification and halo effects near edges.</P>
Low-light image enhancement using variational optimization-based retinex model
Seonhee Park,Soohwan Yu,Byeongho Moon,Seungyong Ko,Joonki Paik IEEE 2017 IEEE transactions on consumer electronics Vol.63 No.2
<P>This paper presents an optimization-based low-light image enhancement method using spatially adaptive l(2)-norm based Retinex model. The proposed method adaptively enforces the regularization parameter using the spatially adaptive weight map, which is generated using the bright channel prior (BCP) and local variance map. Since the proposed weight map assigns the smaller weight value at the bright and edge region, the proposed method can perform weak noise reduction to preserve the edges and textures. In addition, the simplified version of the proposed method is presented using the FFT and quantized weight values for the application to consumer devices. Experimental results show that the proposed method can provide better enhanced result without the l(2)-norm minimization artifacts at the low computational cost.</P>