• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.153-156
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• 2006

The domestic solar radial ion data have been measured at 16 different sites all over the country since the beginning of 1980. It is very important that the fundamental data for the estimation and assessment of local solar radiation can be secured this project. In order to estimate available energy resource from solar radiation, it is necessary to have enough data, more than 30 years In any country. However since we have collected solar radiation(global radial ion including direct normal radiation) data only for 10 years we still need to measure insolation to secure the reliability and standardization of measured local solar radial ion data. In brief, the major activities on this R&D include rout me maintenance of the national network for insolation data measurement, evaluation of the collected data, and reliability enhancement for assessing the quality of solar radiation data as well.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.242-243
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• 2010

Reducing compression artifacts such as ringing and blocking is one of important issues to improve a visual quality of a JPEG compressed image. In this paper, we propose a new post processing technique based on bilateral filtering (BF), which is one of the techniques that are used to reduce compression artifacts. An important issue with the application of the BF is the selection of the filter parameters, which affects the result significantly. In this work, we suggest a new method to select the filter parameter automatically. In addition to artifact reduction using the BF, a contrast enhancement is performed to overcome the contrast loss problem due to compression. The experimental result shows that the proposed approach can alleviate the artifacts efficiently.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.127-130
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• 2008

A 2.2" QVGA($320{\times}240$) 262,114 color AMOLED module has been developed using digital driving methodology. In this paper, we discuss the development of diver IC which is applied to Digital AMOLED module. Technologies for low cost IC structure and image quality enhancement are presented.

• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.106-109
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• 2003

The repeatability error creeps in every corner of mechanical design as mechanical design becomes diverse and complicated. Inkjet printing has inherent repeatability error problem due to its nature of seamless incremental image synthesis of partial images. Without the calibration for the repeatability error realization of high print quality or enhancement of other printing performance could be impaired. Printer designers have met this recurrent problem even before the inception of inkjet print device and contrived various solutions as their own intelectual proprietary. Also, it is a trend to perform necessary calibration without painstaking human intervention. To come up with another useful and proprietary solution has become an important ingredient in inkjet printer design. This paper presents such a solution developed at Digital Printing Division of Samsung Electronics Company.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.173-180
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• 2003

The modified Wiener filtering method is proposed for effective noise suppression in edge region of images corrupted by additive white gaussian noise. Although the pixels classified as a edge region in the conventional Wiener filter have lots of noise components, the conventional Wiener filler cannot remove noise effectively due to the preserving of edges. To reduce noise well in edge region, we modify filter coefficients of the conventional Wiener filter The modified filter coefficients increase in noise suppression effect In edge region, while they preserve edges for strong edge region. From simulation $(256{\time}256$ size, 256 graylevel images) filtered images by the proposed method show much improved subjective image quality with some improved peak signal-to-noise ratio compared to those by the conventional Wiener filtering.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.997-1000
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• 2007

Achieving white balance is one of the key issues for LCD image quality enhancement. A well-known color correction algorithm is Accurate Color Capture (ACC). Determination of ACC correction values has been time consuming as past methods have required trial-and-error analysis of differences between predicted and measured values. We propose a new ACC value determination method that uses spatially emulated patterns and measured values on patterns.

• Journal of Digital Contents Society
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• v.5 no.1
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• pp.79-86
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• 2004

In this paper we implemented the Real Time Contrast Enhancer for image quality enhancement of moving picture. Also we proposed adaptive contrast method that use mean and variance of input video signal. The Designed the contrast Enhancer is measured in comparison with conventional picture and interfaced to 30inch TFT LCD TV of the LG Electronics.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.49-50
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• 2011

In this paper we collect data concerning sleep environments in a bedroom and analyze the relationship between the collected condition data and sleep. In addition, this paper detects scene changes from the subjects in a sleeping state and presents the physical conditions, reactions during sleep, and physical sensations and stimuli. To detect scene changes in image sequences, we used color histogram for the difference between the preceding frame and the current frame. In addition, to extract the tossing and turning for different situations, the subjects were instructed to enter the level of fatigue, the level of drinking, and the level of stomach emptiness.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.217-220
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• 2022

본 논문에서는 CCTV 영상 화질을 향상하고 해상도를 높이기 위해 딥 러닝(Deep Learning)을 이용하여 잡음 제거(Denoising) 와 초해상도(Super-resolution) 작업을 수행한다. 데이터 증강(Data Augmentation)을 통한 초해상도 성능 향상을 위해서 잡음 제거 네트워크의 출력 영상을 초해상도 네트워크의 입력으로 사용하는 순차적 작업을 사용한다. 또한 딥 러닝을 이용한 영상처리에서 발생하는 평균 밝기 오차 문제를 해결하기 위한 손실함수(Loss Function)와 두 가지 이상의 순차적인 딥 러닝 작업에서 발생하는 문제점을 극복하기 위한 손실함수를 제안한다. 제안하는 손실함수는 네트워크의 출력 영상과 타겟 영상의 밝기 오차를 줄이는 것이 가능하고, 순차적 작업에서 보다 정확한 모델 성능 판단이 가능하다.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.237-243
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• 2007

In this paper, we propose the Real-time Dead-Pixel Detection and Compensation System for mobile camera and its hardware architecture. The CMOS image sensors as image input devices are becoming popular due to the demand for miniaturized, low-power and cost-effective imaging systems. However a conventional Dead-Pixel Detection Algorithm is disable to detect neighboring dead pixels and it degrades image quality by wrong detection and compensation. To detect dead pixels the proposed system is classifying dead pixels into Hot pixel and Cold pixel. Also, the proposed algorithm is processing line-detector and $5{\times}5$ window-detector consecutively. The line-detector and window-detector can search dead pixels by using one-dimensional(only horizontal) method in low frequency area and two-dimensional(vertical and diagonal) method in high frequency area, respectively. The experimental result shows that it can detect 99% of dead pixels. It was designed in Verilog hardware description language and total gate count is 23K using TSMC 0.25um ASIC library.