• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.288-299
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• 2001

In transcoding, simply reusing the motion vectors extracted from an incoming video bit stream may not result in the best quality because the incoming motion vectors become non-optimal due to the reconstruction errors. To achieve the best video quality possible, a new motion estimation should be performed in the transcoder. An adaptive motion vector refinement is proposed that refines the base motion vector according to the activity of macroblock using intermediate data extracted from an incoming video bit stream. Experimental results shows that the proposed method can improve the video quality to the level achieved by using the full-scale motion estimation with minimal computational complexity.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.310-319
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• 2016

This paper proposes an effective FRUC (Frame Rate Up-Conversion) technique, which is based on ROI (Region Of Interest) separations and adaptive motion vector refinement. In this paper, in order to overcome the weakness of the EBME (Extended Bi-lateral Motion Estimation) algorithm, which is widely known in FRUC techniques, first, the proposed algorithm performs a bi-directional motion estimation for the complementary asymmetric region. Then, the proposed algorithm classifies each block into ROI or non-ROI block and refine motion vectors in accordance with their block characteristics to have a higher accuracy than the conventional EBME algorithm, specially, for the occlusion regions. The experimental results show that the proposed algorithm can improves 0.59dB on average PSNR as compared to the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.355-363
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• 2011

Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.810-813
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• 2007

Recently, mobile video communication is getting more and more popular. Visual quality and computational complexity are primary factors affecting performance of video communication. Frame rate up-conversion (FRC) is necessary for achieving high visual quality in mobile projection displays. In this paper, a FRC method using motion compensation based on block matching algorithm (BMA) with adaptive block size is proposed. In order to improve the accuracy of the estimated motion vectors, the motion vector refinement technique is proposed. Experiment results indicate that the proposed technique exhibits better performance with lower hardware complexity compared to the conventional methods.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.270-285
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• 2005

A joint design scheme is proposed to optimize the up/down scaler and the motion vector estimation module in the transcoder system. The proposed scheme first optimizes the resolution scaler for a fixed motion vector, and then a new motion vector is estimated for the fixed scaler. These two steps are iteratively repeated until they reach a local optimum solution. In the optimization of the scaler, we derive an adaptive version of a cubic convolution interpolator to enlarge or reduce digital images by arbitrary scaling factors. The adaptation is performed at each macroblock of an image. In order to estimate the optimal motion vector, a temporary motion vector is composed from the given motion vectors. Then the motion vector is refined over a narrow search range. It is well-known that this refinement scheme provides the comparable performance compared to the full search method. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional systems. We can also see that the algorithms exhibit significant improvement in the minimization of information loss compared with other techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.113-118
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• 2012

In this paper, we propose the removal of search point using motion vector correlation and distance between reference frames in H.264/AVC. We remove the search points in full search method and predictive motion vectors in enhanced predictive zonal search method. Since the probability that the reference frame far from the current frame is selected as the best reference frame is decreased, we apply the weighted average based on distance between the current and reference frame to determine the fianl search range. In general, the size of search range is smaller than initial search range. We reduce motion estimation time using the final search range in full search method. Also, the refinement process is adaptively applied to each reference frame. The proposed methods reduce the computational throughput of full search method by 57.13% and of enhanced predictive zonal search by 14.71% without visible performance degradation.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.348-356
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• 2005

In this paper, we propose a fast bitrate reduction transcoding method to convert a bitstream coded by H.264 into a lower bitrate H.264 bitstream. Block mode informations and motion vectors generated by H.264 decoder are used for probability-based block mode determination in the proposed transcoding method. And the motion vector reuse and motion vector refinement process are applied in the proposed transcoding. In the experiment results, the proposed methods achieves approximately 40 times improvement in computation complexity compared with the cascaded pixel domain transcoding, while the PSNR(Peak Signal to Noise Ratio) is degraded with only $0.1\~0.3$ dB.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.329-336
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• 2017

In video compression, Motion Estimation(ME) limits the performance of image quality and generated bit rates. However, it requires much complexity in the encoder part. Multi-view video uses many cameras at different positions. Multi-view video coding needs huge computational complexity in proportion to the number of the cameras. To reduce computational complexity and maintain the image quality, an effective motion estimation method is proposed in this paper. The proposed method exploiting the characteristics of motion vector distribution and the motion of video. The proposed is a kind of a hierarchical search strategy. This strategy consists of multi-grid rhombus pattern, diagonal pattern, rectangle pattern, and refinement pattern. Experiment results show that the complexity reduction of the proposed method over TZ search method and PBS (Pel Block Search) on JMVC (Joint Multiview Video Coding) can be up to 40~75% and 98% respectively while maintaining similar video image quality and generated bit rates.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.280-289
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• 2010

The H.264/AVC standard uses efficient inter prediction technologies improving the coding efficiency by reducing temporal redundancy between images. However, since H.264/AVC does not efficiently encode a video sequence that occurs a local illumination change, the coding efficiency of H.264/AVC is decreased when a local illumination change happens in video. In this paper, we propose an improved motion compensation using adjacent pixels and motion vector refinement to efficiently encode local illumination changes. The proposed method always improves the BD-PSNR (Bj$\o$ntegaard Delta Peak Signal-to-Noise Ratio) of 0.01 ~ 0.21 dB compared with H.264/AVC.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.613-616
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• 2010

본 논문에서는 새로운 움직임 추정(motion estimation, ME) 방식을 사용한 프레임 비율 변환(frame rate conversion, FRC) 기법에 대해 제안한다. 기존의 프레임 비율 변환을 위한 움직임 추정 방식은 영상 압축에서 사용되고 있는 SAD를 사용하여 블록(block) 단위로 움직임 벡터를 추정하는 방식에 기초를 두고 있다. 그러나 잔여 신호(residual signal)를 저장하는 영상 압축과 달리, 잘못된 움직임 추정은 합성된 출력 영상에서 심각한 품질 저하를 가져올 수 있다. 이를 보완하기 위해 움직임 개선(motion refinement, MR)이 사용되고 있지만, 근본적인 해결을 위해서는 정확한 움직임 추정 알고리즘 사용이 필요하다. 특히 SAD를 통한 움직임 추정은 고르지 못한 움직임 벡터장(motion vector field, MVF)을 형성할 수 있으며, 종래의 연구에서 이를 해결하기 위해 SAD(sum of absolute difference)에 벡터의 공간제약(spatial constraint) 항목을 추가하여 비교적 고른 움직임 벡터장을 형성하는 방식이 제시되었다. SAD와 공간 제약 항목의 반영 비율에 따라 움직임 벡터의 중요성과 움직임 벡터장의 일관성이 서로 상충하는데, 기존의 방식은 이 비율을 일정한 상수(constant)값을 사용하고 있으며, 이러한 방식은 이미지의 특성에 따라 결과가 달라진다. 본 논문에서는 SAD와 공간 제약 항목 사이의 반영 비율을 이미지의 특성에 적응하는 방식을 사용하는 움직임 예측을 제시하고, 수행한 결과를 기존의 방식에 의한 결과와 비교하였다.