• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.125-133
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• 2008

Motion blur is a blurring effect on an image caused by the relative motion between the camera and objects in the scene. When an image is captured, motion blurs are caused by relative motion between the camera and the scene. When different objects are moving at different speeds, the characteristics of the blur effect for each object appear differently. To restore the spatially variant blurred image, each of the blur extents should be identified. In this paper, we propose a new method for the identification of blur extent locally using RATS from the image in which the spatially variant motion blur is caused Experiment shows that the proposed algorithm successfully segments the objects with different blurs and identifies the blur extents quite well.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.693-696
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• 2008

Motion blurs are caused by relative motion between the camera and the scene. The blurred image needs to be restored because undesired blur effect degrades the quality of the image. In this paper, we propose a new method for the identification of blur parameters. Experiment shows that the proposed method identifies blur extent regardless of the size of the blur and the object in the original image.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1251-1259
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• 2007

Motion blurs are caused by relative motion between the camera and the scene. The blurred image needs to be restored because undesired blur effect degrades the quality of the image. In this paper, we propose a new method for the identification of blur extent. Experiment shows that the proposed method identifies blur extent regardless of the size of the blur and the object in the original image.

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.169-180
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• 2007

When an image is captured, motion blurs are caused by relative motion between the camera and the scene, In the case of the camera is moving, the extents of the motion blur are spatially variant according to distances from the camera to the objects. Although the camera is fixed, the extents of the motion blur are spatially variant according to various speeds of the moving objects. Unexpected blur effect very often degrades the quality of the image and it needs to be restored, To restore the spatially variant blurred image, each of the point spread function (PSF) should be identified, In this paper, we propose a new method for the identification of blur extent locally from the image in which the spatially variant motion blur is caused. Experiment shows that the proposed method identifies blur extent well.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.721-723
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• 2003

오늘날 2D 그래픽 게임 개발에서 점차적으로 3D 그래픽 게임을 만들게 되는 추세이다. 3D 그래픽 게임의 문제는 역시 그래픽 처리 속도이다. 많은 3D 그래픽 게임 개발사들이 제한된 하드웨어의 성능으로 인하여 표현에 한계를 받고 있는 것이 사실이다. 또한 하드웨어의 발달의 3D 그래픽 게임을 즐기는 게임 유저들에게 보다 나은 게임 환경에 대한 욕구가 늘어나게 된 것이다. 3D 그래픽 게임에 화려하고 멋진 그래픽 기술들이 존재한다. 그러한 기술들은 고성능의 하드웨어를 요구하는 것들이 많고 실제적으로 게임에서 사용되는 데는 많은 어려움을 가지고 있다. 본 논문에서는 이러한 어려운 문제점의 하나인 Motion Blur Effect의 문제점을 파악하고 이를 해결 할 수 있는 방법들을 모색하고자 하였으며 3D 그래픽 게임에서의 Motion Blur Effect 의 가장 큰 문제점인 게임 속도의 전반적인 속도 저하를 해결하는 방법과 프로그램 디자인과 프로그램 구현을 Offscreen Buffer를 이용하는데에 초점을 두었다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.77-83
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• 1998

Generally a moving picture suffers from motion blur, due to relative motion between moving objects and the image formation system. The purpose of this paper is to propose teh model for the motion blur and the restoration method using the regularized iterative technique. In the proposed model, the boundary effect between moving objects and background is analyzed mathematically to overcome the limit of the spatially invariant model. And we present the motion-based image segmentation technique for the object-based image restoration, which is the modified version of the conventional segmentation method. Based on the proposed model, the restoration technique removes the motion blur by using the estimated motion parameter from the result of the segmentation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.130-139
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• 2014

Undesired camera shaking can make a blur effect, which causes a degradation of video quality. We propose an efficient method of removing the blur effects on video captured from a single camera. The proposed method has a sequential process that is applied to each frame. The first stage is to estimate the camera motion for each frame. In order to estimate the camera motion, we compute the optical flow using 3 consecutive frames. Then a patch-wise image deconvolution is applied. During the deconvolution, edge prediction is used to improve the quality of image deconvolution. After patch-wise image deconvolution, deblurred patches are integrated into an image to produce a deblurred frame. The above process is performed for each frame. The experimental result shows that the proposed method removes the blur effect efficiently.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.1-11
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• 2008

This paper proposes a real-time method using a 3-axis accelerometer to enhance blurred images taken from a camera loaded in mobile devices. Blurring phenomenon is a smoothing effect occurring in photo images. Algorithms to cope with blurring phenomenon is essential since small-size mobile devices tremble severely by even a tiny hand-shaking of a user. In this paper, accurate sensing characteristics of the 3-axis accelerometer is acquired by applying the sensor in pendulum motion and the blurring phenomenon is modeled as a uniform distribution and Gaussian distribution. Also, non-Gaussian distributed model is observed in the experiment of real blurring phenomenon and a particular deblurring function is designed by reversing the model. It has been demonstrated that the application of trembling information to the deblurring function adequately removes the blurring phenomenon.

• Transactions on Electrical and Electronic Materials
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• v.8 no.4
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• pp.166-169
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• 2007

In applying LCD to TV application, one of the most significant factors to be improved is image sticking on the moving picture. LCD is different from CRT in the sense that it's continuous passive device, which holds images in entire frame period, while impulse type device generate image in very short time. To reduce image sticking problem related to hold type display mode, we made an experiment to drive TN-LCD like CRT. We made articulate images by turn on-off backlight, and we realized the ratio of Back Light on-off time by counting between on time and off time for video signal input during 1 frame (16.7 ms). Conventional CCFL (cold cathode fluorescent lamp) cannot follow fast on-off speed, so we evaluated new fluorescent substances of light source to improve residual light characteristic of CCFL. We realized articulate image generation similar to CRT by CCFL blinking drive and TN-LCD overdriving. As a result, reduced image sticking phenomenon was validated by naked eye and response time measurement.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.43-48
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• 2014

Usually, image deconvolution is applied as a preprocessing step in surveillance systems to reduce the effect of motion or out-of-focus blur problem. In this paper, we propose a blind-image deconvolution filtering approach based on genetic programming (GP). A numerical expression is developed using GP process for image restoration which optimally combines and exploits dependencies among features of the blurred image. In order to develop such function, first, a set of feature vectors is formed by considering a small neighborhood around each pixel. At second stage, the estimator is trained and developed through GP process that automatically selects and combines the useful feature information under a fitness criterion. The developed function is then applied to estimate the image pixel intensity of the degraded image. The performance of developed function is estimated using various degraded image sequences. Our comparative analysis highlights the effectiveness of the proposed filter.