• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.19-25
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• 2023

In this paper, we propose a method for improving raw images captured in a low light condition based on deep learning considering the image signal processing. In the case of a smart phone camera, compared to a DSLR camera, the size of a lens or sensor is limited, so the noise increases and the reduces the quality of images in low light conditions. Existing deep learning-based low-light image processing methods create unnatural images in some cases since they do not consider the lens shading effect and white balance, which are major factors in the image signal processing. In this paper, pixel distances from the image center and channel average values are used to consider the lens shading effect and white balance with a deep learning model. Experiments with low-light images taken with a smart phone demonstrate that the proposed method achieves a higher peak signal to noise ratio and structural similarity index measure than the existing method by creating high-quality low-light images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2343-2348
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• 2006

Image magnification is among the basic image processing operations. The most commonly used technique for image magnification are based on interpolation method(such as nearest neighbor, bilinear and cubic interpolation). However, the magnified images produced by the techniques that often appear a variety of undesirable image artifacts such as 'blocking' and 'blurring' or too takes the processing time into the several processing for image magnification. In this paper, we propose image magnification method which uses input image's sub-band information such as edge information to enhance the image magnification method. We use the whole image and not use the one's neighborhood pixels to detect the edge information of the image that isn't occurred the blocking phenomenon. And then we emphasized edge information to remove the blurring phenomenon which incited of edge information. Our method, which improves the performance of the traditional image magnification methods in the processing time, is presented. Experiment results show that the proposed method solves the drawbacks of the image magnification such as blocking and blurring phenomenon, and has a higher PSNR and Correlation than the traditional methods.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.317-321
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• 2013

Due to growth of electronics and control devices, automation and situational awareness systems have been applied by automobile. Vision systems with the introduction of unmanned system were being actively developed. In this paper, the distortion in the 7-inch LCD screen for the treatment process are divided into Online and Offline processing. Offline processing based on the image signal processing and for generating LUT Online to Offline generated by processing the distortion is applied to the LUT. LUT is applied to distort the image processing in real time, so that distortion correction is made for the purpose of setting.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.449-452
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• 1998

In this study, the basic image-board and algorithm has been developed to extract a road lane by modeling the driving process. The high speed processing enables an image capture, processing and prompt decision making. In order to high speed processing ASIC like FPGA was designed and integrated in one board system. The algorithm enabling road driving must recognize a straight and bend edge separately. The high speed image processing board using FPGA can be used in real-time decision makeing system for road driving and in the machine vision under bad working environments like a coal mine. And it also can be used in the safety control system in subway and in image input system of CCTV and CATV by designing the board to meet various user's needs.

• Publications of The Korean Astronomical Society
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• v.10 no.1
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• pp.135-146
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• 1995

We have developed a graphic software for image processing of astronomical data obtained by observational equipment in Astronomical Observatory of Kyung Hee University. The essential hardware for running our computer program is simply composed of a PC with the graphic card to handle 256 colors and the color graphic monitor, including CCD camera system. Our software has been programmed in WINDOWS to provide good environments for users, by using various techniques of image processing on astronomical image data recorded in FITS format by KHCCD program(Jin and Kim, 1994) with a compressional mode. We are convinced that our results will be a fundamental and useful technique in the construction of data processing system and can be effectively used in any other observatories, as well as in data processing system of Kyung Hee University.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.247-253
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• 2012

This paper presents sensor network based autonomous vehicle system using a proposed image processing algorithm. The proposed image processing algorithm consists of pre-processing and five-stage image processing: coordinate calculation, driving area decision, line segment calculation, steeling decision, and acceleration decision. We evaluate the performance of the proposed algorithm on both straight road and curved road. Experimental results indicate that the proposed algorithm works well for autonomous vehicles. However, control accuracy of the proposed algorithm decreases as speed is increasing.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.295-295
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• 2000

In this paper, the measurement algorithm of PCB alignment error is developed using image processing. The X-Y-$\theta$ table correcting PCB alignment error is driven by drive module based on microprocessor according to calculation results obtained through image processing procedure. In order to recognize the X-Y-$\theta$ position errors, two fiducial points are marked on PCB and two cameras of ultraviolet rays types are used for detection of the points to capture exactly fiducial points under disturbance of illumination change. Through application for a practical screen printer, the precision control using the developed position control system can be realized about 2.5${\mu}{\textrm}{m}$ in table moving range and 8${\mu}{\textrm}{m}$ in camera processing precision.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.867-870
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• 2000

영상에서 나타난 컬러 정보를 이용해 검색을 수행하고자 하는 연구 방법에서 일반적으로 적용되어 사용되어진 방법 중 하나로 컬러 히스토그램의 유사성을 이용한 매핑을 들 수 있다. 이 방법의 장점은 쉽게 영상에서 나타난 컬러 정보를 그룹화하여 매핑 할 수 있게 해주나, 전체 영상에서 나타난 컬러의 양 정보만을 제공할 뿐, 각각의 컬러에 대한 공간적 정보를 제공하지는 못한다. 즉, 동일한 컬러가 한 곳에 집중해서 나타난 영상과 분산되어 나타난 영상이 동일한 컬러 정보로 매핑되므로 원치 않는 검색 결과를 얻게 된다. 이러한 문제점을 해결하기 위해 기존의 방법은 컬러 히스토그램에서 얻어진 컬러 정보와 별개의 공간 정보 추출 알고리즘을 통해 얻어진 정보를 결합(fusion) 하여 문제를 해결하였다. 본 연구에서는 이러한 단점을 해결하기 위해 각각의 히스토그램의 빈(bin)들에 컬러에 대한 양 정보만이 아니라 컬러의 중심점과 분산 값 정보를 구하여 이를 영상 검색을 위한 매핑 정보로 사용한다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2707-2715
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• 1999

Recently, there have been researches to automate processing and analysing images in the medical field using image processing technique, a fast communication network, and high performance hardware. In this paper, we propose a system to be able to analyze morphological abnormality of red-blood cells for peripheral blood image using image processing techniques. To do this, we segment red-blood cells in the blood image acquired from microscope with CCD camera and then extract UNL fourier features to classify them into 15 classes. We reduce the number of multi-variate features using PCA to construct a more efficient classifier. Our system has the best performance in recognition rate, compared with two other algorithms, LVQ3 and k-NN. So, we show that it can be applied to a pathological guided system.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.443-445
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• 2022

광원 자체의 밝기가 낮거나 드리워진 그림자 등의 이유로 어두운 영역을 포함하고 있는 저조도 영상으로 인해 물체의 식별이 어려운 상황을 일상생활에서 겪게 된다. 본 논문에서는 조명 성분의 영향을 줄이고 객체의 특징을 표현하는 반사 성분을 강조하여 화질을 개선한다. 또한 촬영하는 카메라와 영상의 물체 사이의 상대적인 움직임으로 발생하는 흐릿한 영역을 최대한 제거해주고 잡음까지 보정이 되는 Stack-attention 기법을 제안한다.