• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.32-39
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• 2002

Vector quantization for image compression needs expensive encoding time to find the closest codeword to the input vector. This paper proposes a search algorithm for fast vector quantization encoding. Firstly, we derive a robust condition based on the efficient topological structure of the codebook to dramatically eliminate unnecessary matching operations from the search procedure. Then, we Propose a fast search algorithm using the elimination condition. Simulation results show that with little preprocessing and memory cost, the encoding time of the proposed algorithm is reduced significantly while the encoding quality remains the same with respect to the full search algorithm. It is also found that the Proposed algorithm outperforms the existing search algorithms.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.887-890
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• 1998

We present a novel multi-resolution block matching algorithm (BMA) for fast motion estimation. At the coarsest level, a full search BMA (FSBMA) is performed for searching complex or random motion. Concurrently, spatial correlation of motion vector (MV) field is used for searching continuous motion. Here we present an efficient method for searching full resolution MVs without MV decimation even at the coarsest leve. After the coarsest level search, two or three initial MV candidates are chosen for the next level. At the further levels, the MV candidates are refined within much smaller search areas. Simulation results show that in comparison with FSBMA, the proposed BMA achieves a speed-up factor over 710 with minor PSNR degradation of 0.2dB at most, under a normal MPEG2 coding environment. Furthermore, our scheme is also suitable for hardware implementation due to regular data-flow.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.242-259
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• 2015

Three-dimensional video coding is one of the main challenges restricting the widespread applications of 3D video and free viewpoint video. In this paper, a novel fractal coding algorithm with motion-vector-field-based motion estimation for depth map sequence is proposed. We firstly add pre-search restriction to rule the improper domain blocks out of the matching search process so that the number of blocks involved in the search process can be restricted to a smaller size. Some improvements for motion estimation including initial search point prediction, threshold transition condition and early termination condition are made based on the feature of fractal coding. The motion-vector-field-based adaptive hexagon search algorithm on the basis of center-biased distribution characteristics of depth motion vector is proposed to accelerate the search. Experimental results show that the proposed algorithm can reach optimum levels of quality and save the coding time. The PSNR of synthesized view is increased by 0.56 dB with 36.97% bit rate decrease on average compared with H.264 Full Search. And the depth encoding time is saved by up to 66.47%. Moreover, the proposed fractal depth map sequence codec outperforms the recent alternative codecs by improving the H.264/AVC, especially in much bitrate saving and encoding time reduction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1231-1238
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• 2005

This paper presents a new fast encoding algorithm for image vector quantization that incorporates the partial distances of multiple features with a multidimensional look-up table (LUT). Although the methods which were proposed earlier use the multiple features, they handles the multiple features step by step in terms of searching order and calculating process. On the other hand, the proposed algorithm utilizes these features simultaneously with the LUT. This paper completely describes how to build the LUT with considering the boundary effect for feasible memory cost and how to terminate the current search by utilizing partial distances of the LUT Simulation results confirm the effectiveness of the proposed algorithm. When the codebook size is 256, the computational complexity of the proposed algorithm can be reduced by up to the $70\%$ of the operations required by the recently proposed alternatives such as the ordered Hadamard transform partial distance search (OHTPDS), the modified $L_2-norm$ pyramid ($M-L_2NP$), etc. With feasible preprocessing time and memory cost, the proposed algorithm reduces the computational complexity to below the $2.2\%$ of those required for the exhaustive full search (EFS) algorithm while preserving the same encoding quality as that of the EFS algorithm.

• 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 the Institute of Electronics Engineers of Korea SP
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• v.40 no.2
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• pp.20-28
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• 2003

Recently we need a faster and more accurate motion vector search algorithm for ASIC(Application Specific IC) or small systems. Block motion estimation using Full Search(FS) algorithm provides the best visual quality and PSNR, but it requires intensive computations. The previously proposed fast algorithms reduced the number of computations by limiting the number of searching locations. This is accomplished at the expense of less accuracy of motion estimation and gives rise to an appreciably higher SAD(Sum of Absolute Difference) for motion compensated images. In this paper we exploit the spatial correlation of motion vectors and present a fast motion estimation scheme which uses the predicted motion vector(PMV). The PMV scheme is more clear and simpler than the previously proposed algorithms which also use adjacent motion vectors. Simulation results with standard video sequences show that the PMV scheme is faster and more accurate than other algorithms such as Nearest-Neighbors Search(NNS) algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.2
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• pp.66-75
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• 2010

This paper proposes an efficient method for design and implementation of the artificial intelligence (AI) of 'omok' game on the GPU. The proposed AI is designed on a cooperative structure using min-max game tree and genetic algorithm. Since the evaluation function needs intensive computation but is independently performed on a lot of candidates in the solution space, it is computed on the GPU in a massive parallel way. The implementation on NVIDIA CUDA and the experimental results show that it outperforms significantly over the CPU, in which parallel game tree and genetic algorithm on the GPU runs more than 400 times and 300 times faster than on the CPU. In the proposed cooperative AI, selective search using genetic algorithm is performed subsequently after the full search using game tree to search the solution space more efficiently as well as to avoid the thread overflow. Experimental results show that the proposed algorithm enhances the AI significantly and makes it run within the time limit given by the game's rule.

• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.317-326
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• 2002

The adaptive coding schemes in H.264 standardization provide a significant ceding efficiency and some additional features like error resilience and network friendliness. The variable block size motion compensation using multiple reference frames is one of the key H.264 coding elements to provide main performance gain, but also the main culprit that increases the overall computational complexity. For this reason, this paper proposes a selective motion estimation algorithm based on variable block size for fast motion estimation in H.264. After we find the SAD(Sum of Absolute Difference) at initial points using diamond search, we decide whether to perform additional motion search in each block. Simulation results show that the proposed method is five times faster than the conventional full search in case of search range $\pm$32.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.483-491
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• 2009

In this paper, we propose a fast motion estimation algorithm using adaptive elimination of sub-block partial coefficients. The proposed algorithm predicts an adaptive threshold for each sub-block by using relationship of an initial sum of absolute difference(SAD) and a minimum SAD at the current point, and efficiently reduces unnecessary calculation time of the conventional partial distortion elimination(PDE) algorithm with the predicted threshold. Our algorithm reduces about 60% of computations of the conventional PDE algorithm without any degradation of prediction quality compared with the con ventional full search. Additionally, the proposed algorithm can be applied to other fast motion estimation 떠gorithms. the proposed Our proposing algorithm will be useful to real-time video coding applications using MPEG-2 or MPEG-4 AVC standards.

• 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.