• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.303-310
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• 2007

Motion Estimation (ME) is a core part of most Video compression systems since it affects directly the output video quality and the encoding time. The most basic method of ME, Full Search (FS) gives the highest visual quality but also has the problem of significant computational load. To solve this problem, many fast algorithm has been proposed. Among them, MVFAST and PMVFAST show impressive results in video quality and the computational load by using the correlation between motion vectors of adjacent blocks. In particular, PMVFAST reduces search points dramatically and also gives very high video quality by using the median predictor. In this paper, we propose a new algorithm that uses the redefined median predictor which reduces the number of search points and yields a high visual quality by reducing the number of thresholds and early termination conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.712-719
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• 2007

In this paper, we propose a new, effective, fast motion estimation algorithms using $4{\times}4$ pixels Hadamard transform. The Hadamard transform has the advantage of simplicity because it uses only addition and subtraction. Motion estimation is composed of three stages. First, it should be decided whether to terminate the search early and use a previous motion vector with DC(Direct Current) coefficients. Then the adaptive matching scan order for motion estimation should be determined according to the image complexity using AC(Alternating Current) coefficients. Experimentally, we adapted this algorithms to MVFAST and PMVFAST algorithms, and the proposed algorithms turn out to be very efficient in terms of computational speed while remaining almost the same in terms of PSNR(Peak Signal-to-Noise Ratio) compared to MVFAST and PMVFAST algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.945-949
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• 2009

This paper proposes an enhanced motion estimation that is one of core parts affecting the coding performance and visual quality in video coding. Although the full search technique, which is the most basic method of the motion estimation, presents the best visual quality, its computational complexity is great, since the search procedures to find the best matched block with each block in the current frame are carried out for all points inside the search area. Thus, various fast algorithms to reduce the computational complexity and maintain good visual quality have been proposed. The PMVFAST adopted the MPEG-4 visual standard produces the visual quality near that by the full search technique with the reduced computational complexity. In this paper, we propose a new motion vector prediction method using median processing. The proposed method reduces the computational complexity for the motion estimation significantly. Experimental results show that the proposed algorithm is faster than the PMVFAST and better than the full search in terms of search speed and average PSNR, respectively.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.53-59
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• 2014

Motion estimation is a core part of most video compression systems since it directly affects the output video quality and the encoding time. The full search (FS) technique gives the highest visual quality but has the problem of a significant computational load. To solve this problem, we present in this paper a modified median (MMED) operation and advanced search strategies for fast motion estimation. The proposed MMED operation includes a temporally co-located motion vector (MV) to select an appropriate initial candidate. Moreover, we introduce a search procedure that reduces the number of thresholds and simplifies the early termination conditions for the determination of a final MV. The experimental results show that the proposed approach achieves substantial speedup compared with the conventional methods including the motion vector field adaptive search technique (MVFAST) and predictive MVFAST (PMVFAST). The proposed algorithm also improves the PSNR values by increasing the correlation between the MVs, compared with the FS method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3697-3705
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• 2011

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose a new prediction search algorithm for block matching using the temporal and spatial correlation of the video sequence and local statistics of neighboring motion vectors. The proposed ANBA(Adaptive Neighboring-Block Search Algorithm) determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(Sum of Absolute Difference) value by the predicted motion vectors of neighboring blocks around the same block of the previous frame and the current frame and use a previous motion vector. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 1.06dB as depend on the video sequences and improved about 0.01~0.64dB over MVFAST and PMVFAST.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1232-1239
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• 2006

In video standards such as MPEG-1/2/4 and H.264/AVC, motion estimation / compensation(ME/MC) process causes the most encoding complexity of video encoder. The full search method, which is used in general video codecs, exhausts much encoding time because it compares current macroblock with those at all positions within search window for searching a matched block. For the alleviation of this problem, the fast search methods such as TSS, NTSS, DS and HEXBS are exploited at first. Thereafter, DS based MVFAST, PMVFAST, MAS and FAME, which utilize temporal or spacial correlation characteristics of motion vectors, are developed. But there remain the problems of image quality degradation and algorithm complexity increase. In this thesis, the proposed algorithm maximizes search speed and minimizes the degradation of image quality by determining initial search point correctly and using simple one-dimension search patterns considering motion characteristics of each frame.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.121-124
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• 2006

본 논문에서는 영상 압축에 있어서 사용되는 새로운 고속 움직임 추정 기법에 대해 소개한다. 전역 탐색 블록 정합 알고리즘(FSBMA)은 최상의 PSNR을 갖는 화질로 움직임 벡터를 추정할 수 있지만 높은 계산량으로 인하여 실시간 구현에 부적합하다는 단점을 가지고 있다. 그러므로 계산량을 낮추면서 유사한 화질을 유지할 수 있는 많은 고속 탐색 기법들이 제안되어 왔다. 본 논문에서는 기존의 잘 알려진 고속 블록 정합 알고리즘을 수정 보완한 새로운 알고리즘을 제안한다. 제안한 방법에서는 움직임 추정에서의 고속 블록 정합 알고리즘에 있어 변형된 다이아몬드(Diamond) 탐색 기법을 이용하여 영상이 갖는 서로 다른 움직임 패턴에 대해 움직임의 방향성에 따라 적응적으로 탐색 방향과 패턴을 달리하면서 움직임을 예측하여 다이아몬드(Diamond)탐색 알고리즘과 유사한 화질을 유지하면서 보다 적은 계산량을 가지고 움직임 벡터를 추정학 수 있다. 또한 이를 PMVFAST(Predictive Motion Vector Field Adaptive Search Technique)와 결합함으로서 보다 좋은 화질을 가질 수 있다.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1142-1149
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• 2004

Motion Estimation(ME) has been developed to reduce temporal redundancy in digital video signals and increase data compression ratio. ME is an Important part of video encoding systems, since it can significantly affect the output quality of encoded sequences. However, ME requires high computational complexity, it is difficult to apply to real time video transmission. for this reason, motion estimation algorithms with low computational complexity are viable solutions. In this paper, we present an efficient method with low computational complexity based on spatial and temporal correlations of motion vectors. The proposed method uses temporally and spatially correlated motion information, the motion vector of the block with the same coordinate in the reference frame and the motion vectors of neighboring blocks around the current block in the current frame, to decide the search pattern and the location of search starting point adaptively. Experiments show that the image quality improvement of the proposed method over MVFAST (Motion Vector Field Adaptive Search Technique) and PMVFAST (Predictive Motion Vector Field Adaptive Search Technique) is 0.01～0.3(dB) better and the speedup improvement is about 1.12～l.33 times faster which resulted from lower computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.520-529
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• 2007

In this paper, we study the characteristics of parameters which are related to performance of MCTF which is a key technique for wavelet-based scalable video coding, and propose an improved MCTF method. The proposed MCTF method adopts the motion estimation of which motion vector field is distributed more uniformly using variable block sizes. By using the proposed method, the decomposition performance of temporal filter is improved, and the energy in high-frequency frames is reduced. It can help the entropy coder to generate lower bitrate. From simulation results, we verify the decomposed energy on high-frequency frame using the proposed method is reduced by 25.86% at the most in terms of variance of the high-frequency frame.