• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.13-20
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• 2004

In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efcient coding techniques that reduce the complexity of the encoder. Until recently, encoder optimization without shape coding has been a major concern in video for wire/wireless low bit rate coding services. Recently, we found out that the computational complexity of MPEG-4 shape coding plays a very important role in the object-based coding through experiments. We have made an experiment whether we could get optimized object-based coding method through successfully combining latest optimized texture coding techniques with our proposed optimized shape coding techniques. In texture coding, we applied the MVFAST method for motion estimation. We chose not to use IVOPF(Intelligent VOP Formation) but to use TRB(Tightest Rectangular Boundary) for positioning VOP and, finally, to eliminate the spiral search of shape motion estimation to reduce the complexity in shape coding. As a result of experiment, our proposed scheme achieved improved time complexity over the existing reference software by $57.3\%$ and over the optimized method on which only shape coding was applied by $48.7\%$, respectively.

• 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.

• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.275-285
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• 2003

The now video coding standard H.264 employs variable block size motion compensation, multiple references, and quarter-pel motion vector accuracy. These techniques are key features to accomplish higher coding gain, however, at the same time main factors that increase overall computational complexity. Therefore, in order to apply H.264 to many applications, key techniques are requested to improve their speed. For this reason, we propose a fast motion estimation which is suited for variable block size motion communication. In addition, we propose a fast mode decision method to choose the best mode at early stage. Experimental results show the reduction of the number of SAT SATD calculations by a factor of 4.5 and 2.6 times respectively, when we compare the proposed fast motion estimation and the conventional MVFAS $T^{［8-10］}$. Besides, the number of RDcost computations is reduced by about 45%. Therefore, the proposed methods reduces significantly its computational complexity without noticeable coding loss.