• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.557-564
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• 2001

In general, several moving regions with different motions coexist in a block located on motion boundaries in the block-based motion estimation. In this case the motion compensation error(MCEs) are different with the moving regions. This is inclined to deteriorate the quality of motion compensated images because of the inaccurate motions estimated from the conventional mean absolute error(MAE) based matching function in which the matching error per pixel is accumulate throughout the block. In this paper, we divided a block into the regions according to their motions using the motion information of the spatio-temporally neighboring blocks and calculate the average MCF for each moving mentioned. From the simulation results, we showed the improved performance of the proposed method by comparing the results from other methods such as the full search method and the edge oriented block matching algorithm. Especially, we improved the quality of the motion compensated images of blocks on motion boundaries.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.317-318
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• 2013

블록정합을 이용한 객체 추적 시 다른 물체에 의한 부분적인 가림이나 잡음 등이 발생할 경우, 추적 성능이 매우 저하될 수 있다. 이는 단순히 두 영상의 밝기를 블록 단위로 비교하여 이동 위치를 판단하기 때문이다. 본 논문에서는 상기 문제점을 해결하기 위해, 객체의 움직임을 예측할 수 있는 필터를 적용한다. 예측된 위치와 가까운 곳에서 계산된 유사도에는 보다 높은 가중치를 곱하여 블록정합을 수행한다. 필터를 통해 예측된 객체 이동은 과거의 움직임을 반영하고 있으므로 일시적인 외란에 대해 추적 능력을 강인하게 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.863-866
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• 2000

본 논문에서는 비디오 코딩을 위한 적응적 블록 정합 알고리즘을 제안한다. 제안 알고리즘에서는 블록내의 움직임 정도에 따라 다단계의 블록 레벨을 설정하고, 그 블록 레벨에 따른 각기 다른 다단계의 움직임 예측을 수행한다. 이는 움직임이 적은 영역에서의 불필요한 탐색과정을 제거하여 계산적 효율성을 증대하고, 움직임 정도가 큰 부분으로 갈수록 움직임 예측 과정을 심화 시켜 예측의 정확성을 증가시킨다 본 제안된 방식을 가지고 실험한 결과 한 프레임 당 적은 수의 블록으로 고정된 크기의 블록을 가진 전역 탐색 블록 정합 알고리즘보다 적은 예측 에러를 발생시켜 1dB 정도의 PSNR 개선을 가져왔고 98% 정도의 연산량 절감 효과가 있는 것으로 나타났다.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.57-58
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• 2011

스테레오 정합 방법에는 크게 영역기반 방식과 특징기반 방식으로 나뉠수 있으며 보통 사용자가 특징점을 입력해야 하는 특징기반보다는 광범위하게 사용할 수 있는 영역기반 방식의 스테레오 정합법이 많이 사용되고 있다. 하지만 영역기반은 해당 영역 즉 블록 단위로 비교를 해야 하기 때문에 실시간 스테레오 정합에는 계산 시간이 많이 걸리게 된다. 따라서 본 연구에서 제안하는 Line Disparity Map 알고리즘은 정합 점을 라인별로 비교하기 때문에 블록 방식보다 빠르고, 라인의 기울기를 바탕으로 정합점을 찾기 때문에 주변환경에 영향을 받지 않는 장점이 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.539-547
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• 2003

According to the PDE scheme, it is desirable to make the value of SAD to be rapidly increased in motion estimation. In this paper, we propose a new block matching algorithm based on the combination of a new scan and search order. In the proposed scan order, a current block is divided by the frequency that is estimated by summing the difference between the mean and the values of the pixels. And then the calculation of SAD is performed from the highest frequency area. In the proposed search order based on DC difference between the current and the candidate block, candidate blocks with low DC are early checked in motion estimation. Simulation results show that the proposed method achieves about 6% computational gain compared with the conventional methods.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.767-774
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• 2002

Conventional research on image restoration has focused on restoring degraded images resulting from image formation, storage and communication, mainly in the signal processing field. Related research on recovering original image information of caption regions includes a method using BMA(block matching algorithm). The method has problem with frequent incorrect matching and propagating the errors by incorrect matching. Moreover, it is impossible to recover the frames between two scene changes when scene changes occur more than twice. In this paper, we propose a method for recovering original images using EBMA(Extended Block Matching Algorithm) and a region compensation method. To use it in original image recovery, the method extracts a priori knowledge such as information about scene changes, camera motion and caption regions. The method decides the direction of recovery using the extracted caption information(the start and end frames of a caption) and scene change information. According to the direction of recovery, the recovery is performed in units of character components using EBMA and the region compensation method. Experimental results show that EBMA results in good recovery regardless of the speed of moving object and complexity of background in video. The region compensation method recovered original images successfully, when there is no information about the original image to refer to.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1903-1904
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• 2008

이 논문에서는 영상 프레임사이의 움직임 벡터 연구에 기반을 둔 빠른 블록 정합 움직임 추정을 위해 보완된 다이아몬드 탐색 알고리즘을 제안한다. 실험 결과는 제안된 알고리즘이 기존의 다이아몬드 탐색 알고리즘 보다 더 적은 탐색으로 좀 더 빠르게 동작하는 것이 가능하다. 본 알고리즘의 특징은 움직임이 적은 블록에 대해서는 CDS(conjugate direction search) 알고리즘을 적용하여 탐색함으로써 탐색 점의 수를 줄일 수 있어 좀 더 빠르게 움직임 추정을 할 수 있다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.102-111
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• 1999

In this paper, we propose a fast full search block matching algorithm using the search region subsampling and the difference of adjacent pixels in current block. In the proposed algorithm, we calculate the lower bound of mean absolute difference (MAD) at each search point using the MAD value of neighbor search point and the difference of adjacent pixels in current block. After that, we perform block matching process only at the search points that need block matching process using the lower bound of MAD at each search point. To calculate the lower bound of MAD at each search point, we need the MAD value of neighbor search point. Therefore, the search points are subsampled at the factor of 4 and the MAD value at the subsampled search points are calculated by the block matching process. And then, the lower bound of MAD at the rest search points are calculated using the MAD value of the neighbor subsampled search point and the difference of adjacent pixels in current block. Finally, we discard the search points that have the lower bound of MAD value exceed the reference MAD which is the minimum MAD value of the MAD values at the subsampled search points and we perform the block matching process only at the search points that need block matching process. By doing so, we can reduce the computation complexity drastically while the motion compensated error performance is kept the same as that of full search block matching algorithm (FSBMA). The experimental results show that the proposed method has a much lower computational complexity than that of FSBMA while the motion compensated error performance of the proposed method is kept same as that of FSBMA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.128-140
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• 2000

In this paper, we propose a fast block matching algorithm using the mean absolute error (MAE) of neighbor search point and search region reduction. The proposed algorithm is composed of two stages. At the first stage,the search region is divided into nonoverlapped 3$\times$3 areas and MAE of the center point of each area iscalculated. The minimum MAE value of all the calculated MAE's is determined as reference MAE. At thesecond stage, because the possibility that final motion vector exist near the position of reference MAE is veryhigh, we use smaller search region than first stage, And, using the MAE of center point of each area, the lowerbound of rest search point of each area is calculated and block matching process is performed only at the searchpoints that the lower bound is smaller than reference MAE. By doing so, we can significantly reduce thecomputational complexity while keep the increasement of motion estimation error small.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1563-1571
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• 2009

In this paper, we propose a new boundary matching method for the temporal error concealment and a post processing algorithm for perceptual quality improvement of the concealed frame. Temporal error concealment is a method that substitutes error blocks with similar blocks from the reference frame. In conventional H.264/AVC standard, it compares outside pixels of erroneous block with inside pixels of reference block to find the most similar block. However, it is very possible that the conventional method substitutes erroneous block with the wrong one because it compares only narrow spatial range of pixels. In this paper, for substituting erroneous blocks with more correct blocks, we propose enhanced boundary matching method by comparing inside and outside pixels of reference block with outside pixels of erroneous block and setting up additional candidate motion vector in the fixed search range based on maximum and minimum value of candidate motion vectors. Furthermore, we propose a post processing method to smooth edges between concealed and decoded blocks without error by using the modified deblocking filter. We identified that the proposed method shows quality improvement of about 0.9dB over the conventional boundary matching methods.