• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.761-767
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• 2003

In this paper, A Fast Multi-level Successive Elimination Algorithm (FMSEA) is presented for block matching motion estimation in video coding. Motion estimation accuracy of FMSEA is equal to that of Multilevel Successive Elimination Algorithm(MSEA). FMSEA can reduce the computations for motion estimation of MSEA by using partial distortion elimination technique. The efficiency of the proposed algorithm was verified by experimental results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.179-187
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• 2009

In this paper, an efficient multi-level successive elimination algorithm using the locality in block was proposed for motion estimation. If SAD(sum of absolute difference) is calculated from large absolute difference values to small absolute difference values, SAD is increased rapidly. So, partial distortion elimination in SAD calculation can be done very early. Hence, the computations of SAD calculation can be reduced. In this paper, an efficient algorithm to calculate SAD from large absolute difference values to small absolute difference values by using the locality in block. Experimental results show that the proposed algorithm is an efficient algorithm with 100% motion estimation accuracy for the motion estimation of motion vectors.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.889-897
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• 2005

This paper presents a new fast motion estimation algorithm for multi-reference frames. We first analyze the experimental results of the successive elimination algorithm, which is a fast version of full search algorithm, being applied to Multi-reference frames. Based on the analysis, a new scheme for alleviating its computational burden is introduced. In the proposed method, the motion vector for the immediately previous reference frame is found by applying the successive elimination algorithm, while the motion vector for other reference frames is estimated by extrapolation of the already obtained motion vector. Adaptively restricting the motion search area to the local area centered on the estimated motion vector, the proposed method provides dramatic computational complexity reduction but slight quality degradation. The proposed method is evaluated by experiments for some image sequences.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1043-1052
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• 2003

In this paper, we present a fast motion estimation algorithm to reduce the computations of block matching algorithm for motion estimation in video coding. The proposed algorithm is based on Multi-level Successive Elimination Algorithm and Efficient Multi-level Successive Elimination Algorithms. The best estimate of the motion vectors can be obtained by hierarchical search point sampling and thus the proposed algorithm can decrease the number of matching evaluations that require very intensive computations. The efficiency of the proposed algorithm was verified by experimental results.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.98-113
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• 2002

In this paper, we present advanced algorithms to reduce the computations of block matching algorithms for motion estimation in video coding. Advanced multi-level successive elimination algorithms(AMSEA) are based on the Multi-level successive elimination algorithm(MSEA)[1]. The first algorithm is that when we calculate the sum of absolute difference (SAD) between the sum norms of sub-blocks in MSEA, we use the partial distortion elimination technique. By using the first algorithm, we can reduce the computations of MSEA further. In the second algorithm, we calculate SAD adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in SAD calculation can occur early. So, the computations of MSEA can be reduced. In the third algorithm, we can estimate the elimination level of MSEA. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is a very fast block matching algorithm with nearly 100% motion estimation accuracy. Experimental results show that AMSEA are very efficient algorithms for the estimation of motion vectors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2A
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• pp.162-168
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• 2007

This paper proposes two detection algorithms for Multi-user Space Time Block Code systems. The first one is linear detection Gaussian Elimination algorithm, and then it combined with Ordered Successive Cancellation to get better performance. The comparisons between receiver and other popular receivers, including linear receivers are provided. It will be shown that the performance of Gaussian Elimination receiver is similar but more simplicity than linear detection algorithms and performance of Gaussian Elimination Ordered Successive Cancellation superior as compared to other linear detection method.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.147-156
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• 2004

In this paper, a new fast motion estimation algorithm which is based on the Block Sum Pyramid Algorithm(BSPA) is presented. The Spiral Diamond Mesh Search scheme and Partial Distortion Elimination scheme of Efficient Multi-level Successive Elimination Algorithm were improved and then the improved schemes were applied to the BSPA. The motion estimation accuracy of the proposed algorithm is nearly 100% and the cost of Block Sum Pyramid Algorithm was reduced in the proposed algorithm. The efficiency of the proposed algorithm was verified by experimental results.

• Journal of the Korea Computer Industry Society
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• v.5 no.5
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• pp.755-760
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• 2004

In this paper, an advanced successive elimination algorithm was proposed using mean absolute difference of neighboring search points. By using mean absolute difference of neighboring search points, the search point in motion estimation can be eliminated effeciently without matching evaluation that requires very intensive computations. By using adaptive MAD calculation algorithm, the candidate matching block can be eliminated early. So, the number of the proposed algrorithm was verified by experimental results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.1-8
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• 2006

This paper presents a fast full search algorithm for motion estimation applicable to multiple reference images. The proposed method is an extended version of the rate constrained successive elimination algorithm (RSEA) for multiple reference frame applications. We will show that motion estimation for the reference images temporally preceding the first reference image can be less intensive in computation compared with that for the first reference image. for computational reduction, we will drive a new condition to lead the smaller number of candidate blocks for the best matched block. Simulation results explain that our method reduces computation complexity although it has the same quality as RSEA.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.275-280
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• 2004

In this paper, a very fast block matching scheme was proposed to reduce the computations of Block Sum Pyramid Algorithm for motion estimation in video coding. The proposed algorithm is based on Block Sum Pyramid Algorithm and Efficient Multi-level Successive Elimination Algorithm. The proposed algorithm can reduce the computations of motion estimation greatly with 100% motion estimation accuracy. The efficiency of the proposed algorithm was verified by experimental results.