• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.43-53
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• 2004

In this paper, we propose a robust deinterlacing algorithm which combines edge dependent interpolation (EDI) and global motion compensation (GMC). Generally, EDI algorithm shows a visually better performance than any other deinterlacing algorithm using one field. However, due to the restriction of information in one field, a high duality progressive image from Interlaced sources cannot be acquired by intrafield methods. On the contrary, since algorithms based on motion compensation make use of not only spatial information but also temporal information, they yield better results than those of using one field. However, performance of algorithms based on motion compensation depends on the performance of motion estimation. Hence, the proposed algorithm makes use of mixing process of EDI and GMC. In order to obtain the best result, an adaptive thresholding algorithm for detecting the failure of GMC is proposed. Experimental results indicate that the proposed algorithm outperforms the conventional approaches with respect to both objective and subjective criteria.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.731-740
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• 2003

Since motion estimation remove the redundant data to employ the temporal correlations between adjacent frames in a video sequence, it plays an important role in digital video coding. And in the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the small-cross search pattern and the block-based gradient descent search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the small-cross search pattern, and then quickly finds the other motion vectors that are not close to the center of search window using the block-based gradient descent search pattern. Through experiments, compared with the block-based gradient descent search algorithm(BBGDS), the proposed search algorithm improves as high as 26-40% in terms of average number of search point per motion vector estimation.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.378-391
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• 2011

In this paper, we suggest a novel method of selecting visual information based on bottom-up visual attention of human. We propose a new model that improve accuracy of detecting attention region by using depth information in addition to low-level spatial features such as color, lightness, orientation, form and temporal feature such as motion. Motion is important cue when we derive temporal saliency. But noise obtained during the input and computation process deteriorates accuracy of temporal saliency Our system exploited the result of psychological studies in order to remove the noise from motion information. Although typical systems get problems in determining the saliency if several salient regions are partially occluded and/or have almost equal saliency, our system is able to separate the regions with high accuracy. Spatiotemporally separated prominent regions in the first stage are prioritized using depth value one by one in the second stage. Experiment result shows that our system can describe the salient regions with higher accuracy than the previous approaches do.

• The Journal of Information Technology
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• v.3 no.2
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• pp.39-47
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• 2000

Among the compression methods of moving picture information, a motion estimation method is used to remove time-repeating. The Block Matching Algorithm in motion estimation methods is the commonest one. In recent days, it is required the more advanced high quality in many image processing fields, for example HDTV, etc. Therefore, we have to accomplish not by means of Partial Search Algorithm, but by means of Full Search Algorithm in Block Matching Algorithm. In this paper, it is suggested a structure that reduce total calculation quantity and size, because the structure using Bit Plane select and use only 3bit of 8bit luminance signal.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.87-97
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• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.293-304
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• 2011

In this paper, we proposed a new hardware architecture for motion estimation (ME) which is the most time-consuming unit among H.264 algorithms and designed to the type of intellectual property (IP). The proposed ME hardware consists of buffer, processing unit (PU) array, SAD (sum of absolute difference) selector, and motion vector (MVgenerator). PU array is composed of 16 PUs and each PU consists of 16 processing elements (PUs). The main characteristics of the proposed hardware are that current and reference frames are re-used to reduce the number of access to the external memory and that there is no clock loss during SAD operation. The implemented ME hardware occupies 3% hardware resources of StatixIII EP3SE80F1152C2 which is a FPGA of Altera Inc. and can operate at up to 446.43MHz. Therefore it can process up to 50 frames of 1080p in a second.

• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.250-265
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• 2007

In this paper, a fast intermode decision scheme is introduced by efficiently performing the mode decision using statistical hypothesis testing for hierarchical B-picture coding of SVC, in which much computational power is expensed for combined variable block sizes and hierarchical B-pictures. The hypothesis testing in the proposed method is performed on $16{\times}16\;and\;8{\times}8$ blocks to have early termination for RD computation of all possible modes. The early termination in intermode decision is performed by comparing the pixel values of current blocks and corresponding motion-compensated blocks. The proposed scheme exhibits effective early termination behavior in intermode decision and leads to a significant reduction up to 69% in computational complexity with slight increment in bit amounts. The degradation of visual quality turns out to be negligible in terms of PSNR values.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.74-77
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• 2010

다시점 비디오 부호화기(MVC)는 다양한 블록 크기 기반의 움직임 추정과 변이 추정을 수행한다. 또한 2개 이상의 다중 참조 영상 움직임 추정 기술을 사용한다. 이 기술들을 통해 MVC는 높은 부호화 효율을 얻을 수 있지만 실제 적용하기에는 너무 높은 부호화 복잡도가 걸림돌로 작용한다. 본 논문에서는 MVC의 부호화 복잡도를 감소시키기 위하여 효율적인 참조 영상 선택 알고리즘을 제안한다. 부호화에 사용된 참조 영상들은 인접한 블록들 간에 높은 상호 연관성을 가지므로, 부호화된 이웃 블록들의 참조 영상 정보를 기반으로 현재 블록의 참조 영상을 효율적으로 선택할 수 있다. 실험을 통해 제안된 알고리즘이 부호화 시간을 기존의 MVC에 비해 최대 73.3%, 평균 57.3% 감소시키며 부호화 효율의 감소는 무시할 만한 수준임을 확인하였다.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.739-742
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• 2001

동영상은 각 프레임 사이에 시간적으로나 공간적으로 많은 양의 정보가 중복되어 있다. 이러한 중복 정보를 줄이는 표현 방법들 중에 하나로, 동영상을 커다란 하나의 영상으로 정합하여 중복 정보를 줄이는 모자이크 기법이 있다. 두 개 이상의 영상을 정합하기 위해서는 영상간의 카메라 파라미터가 필요한데, 본 논문에서는 Mellin 변환을 사용하여 카메라 파라미터를 구하였다. 이때 3차원 공간모델은 직교 투사법을 사용하였으며, 영상의 움직임 모델로는 4개의 파라미터(평행이동, 확대/축소, 회전)를 사용한 어파인 움직임 모델을 사용하였다. 이렇게 구현된 파노라마 영상은 동영상에서 움직이는 물체를 검출하거나 추적하고, 동영상을 편집하는데 응용될 수 있다. 또한 본 연구의 최종 목적인 3D 영상의 배경을 구현하는 데 좀 더 사실적인 영상을 제공할 수 있다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.215-218
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• 2000

디지털 비디오 데이터를 효율적으로 브라우징 하는데 필요한 비디오 분할에 관한 연구가 활발하게 진행되고 있다. 본 연구에서는 비디오 데이터를 Shot단위로 분할하고, Shot내부에서 카메라 동작과 객체 움직임 분석을 이용한 sub-shot으로 분할하고자 한다. 연구 방법으로는 I-frame의 DC 영상을 이용하여 픽쳐그룹을 Shot(장면이 바뀐 경우), Move(카메라 동작,객체움직임), Static(영상의 변화가 거의 없는 경우)로 세분화하고 해당 픽쳐 그룹의 P, B-frame을 검사하여 정확한 컷 발생 위치, 디졸브, 카메라동작, 객체 움직임을 검출하게 된다. 픽쳐그룹 분류에서 정확성을 높이기 위해 계층적 신경망과 다중 특징을 이용한다. 정확한 컷 발생위치 검출하기 위해서 P, B프레임의 메크로블럭 타입을 이용한 통계적 방법을 이용하고, 디졸브, 카메라 동작, 객체 움직임을 검출하기 위해서 P, B-frame의 메크로블럭 타입과 움직임 벡터를 이용한 신경망으로 검출한다. 본 연구에서는 계층적 탐색을 이용하여 시간을 단축할 수 있고, 계층적 신경망과 다중 특징을 이용하여 픽쳐 그룹을 세분화 할 수 있고, 메크로 블록 타입과 통계적 방법을 이용하여 정확한 컷 검출을 할수 있고, 신경망을 이용하여 디졸브, 카메라 동작, 객체움직임을 검출 할 수 있음을 확인한다.