• 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.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.399-402
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• 2011

카메라를 이용하여 정지 영상을 획득할 때 발생할 수 있는 모션 블러 (motion blur) 현상을 보정하기 위해서는 정확한 블러파라미터 (블러의 방향, 블러의 크기)의 추정이 가장 중요하다. 본 논문에서는 블러된 영상의 로그 스펙트럼 (log spectrum)의 비등방성 (anisotropic)과 엔트로피 (Entropy) 특성에 기반한 블러 파라미터 추정 방법을 제안한다. 제안하는 기법은 1D 로그스펙트럼을 이용한 비등방성의 효과적인 분석과 블러 크기의 정확도를 증가시키기 위한 보상 과정을 포함한다. 실험 결과를 통해 제안하는 기법이 단일 영상에서의 등속 직선 운동의 모션 블러 현상을 더 효과적으로 보정하는 것을 보였다.

• 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 Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.53-54
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• 2011

본 논문에서 우리는 동영상에서 인접한 블러되지 않은 참조 프레임을 이용하여 모션 블러를 제거하는 기법을 제안한다. 기존의 디블러링 방법들은 주로 단일 영상을 이용한 방법들로 정확한 커널을 예측하는 것과 원본 영상에 준하는 영상을 복원하는 것에 한계가 존재한다. 하지만 동영상에서 부분적인 프레임에만 블러가 발생한 특수한 경우에는 인접한 위치에 존재하는 블러되지 않은 프레임을 활용하는 것이 가능하다. 제안하는 방법은 블러된 프레임과 인접한 위치에 존재하는 블러되지 않은 프레임 사이에 움직임을 추정하고, 움직임 보상된 영상을 이용하여 커널을 추정한다. 또한 움직임 오차에 따른 잔여 오차 성분에 대해서만 디컨벌루션을 적용하여 물결현상이 억제된 최종적인 결과 영상을 생성한다. 실험 결과는 제안한 방법이 기존의 디블러링 기법에 비해 에지 부분을 잘 복원시키면서 물결현상은 감소된 보다 우수한 디블러링 결과를 가져오는 것을 보여준다.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.219-220
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• 2014

스마트폰과 같은 모바일 기기의 사용이 확대되면서, 보다 쉽게 다양한 멀티미디어 콘텐츠를 획득하고 유통할 수 있게 되었다. 하지만, 획득 과정에서 이미지는 디포커스 및 움직임에 의해 블러해질 수 있다. 이와 같은 블러를 측정하기 위해, 다양한 선명도 평가 기법들이 제안되었다. 하지만, 대부분의 기존 기법들은 디포커스 블러의 특성에 따라 설계되어졌다. 따라서, 본 고에서는 주파수 분석에 기반하여 움직임 블러 이미지의 선명도를 평가하기 위한 알고리즘을 제안한다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.27-33
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• 2009

We propose an efficient method for single image motion deblurring using edge prediction. Previous methods for motion deblurring from a single image have been based on total variation or natural image statistics. In contrast, our method predicts sharp edges by applying bilateral and shock filters and manipulating image gradients directly, and estimates motion blur using the predicted sharp edges. Sharp edge prediction makes our method possible to deblur efficiently with less computation. Results show that our method can effectively and efficiently restore images degraded by large complex motion blur.

• Journal of Korea Game Society
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• v.17 no.1
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• pp.17-26
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• 2017

Several algorithms have been introduced to render motion blur in real time by solving the visibility problem in the spatio-temporal domains. However, some algorithms render at interactive frame rates but have artifacts or noise. Therefore, we propose a new algorithm that renders real-time motion blur using extruded triangles. Our method uses two triangles in the previous and the current frame to make an extruded triangle then send it to the rasterization. To solve the occlusion between extruded triangles for a given pixel, we introduce a combining solution using a sorting in front to back order and bitwise operations in the spatio-temporal dimensions.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.80-84
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• 2014

Dark channel prior means that, for undistorted outdoor images, at least one color channel of a pixel or its neighbors have values close to 0, and thus the prior can be used to estimate the amount of distortion for given distorted images. In other words, if an image is distorted by blur, its dark channel values are averaged with neighbor pixel values and thus increase. This paper proposes a method that estimates blur strengths by analyzing the variation of dark channel values caused by blur. Through experiments with images distorted by Gaussian and horizontal motion blur with given strengths, the usefulness of the proposed method is verified.