• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.278-281
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• 2009

In this paper, we propose a fast partial distortion algorithm using normalized dithering matching scan to get uniform distribution of partial distortion which can reduce only unnecessary computation significantly. Our algorithm is based on normalized dithering order matching scan and calibration of threshold error using LOG value for each sub-block continuously for efficient elimination of unlike candidate blocks while keeping the same prediction quality compared with the full search algorithm. Our algorithm reduces about 60% of computations for block matching error compared with conventional PDE (partial distortion elimination) algorithm without any prediction quality, and our algorithm will be useful to real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1439-1445
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• 2007

In this paper, we propose a fast motion estimation algorithm using initial matching errors by sorting square sub-blocks to find complex sub-block area adaptively based on partial calculation of SAD(sum of absolute difference) while keeping the same prediction quality compared with the PDE(partial distortion elimination) algorithm. We reduced unnecessary calculations with square sub-block adaptive matching scan based initial SAD calculation of square sub-block in each matching block. Our algorithm reduces about 45% of computations for block matching error compared with conventional PDE(partial distortion elimination) algorithm without any degradation of prediction quality, and for algorithm will be useful to real-time video coding applications using MPEG-4 AVC or MPEG-2.

• 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 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 Communications and Networks
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• v.12 no.1
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• pp.5-10
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• 2010

This paper introduces a new fast motion estimation based on estimating a block matching error (i.e., sum of absolute difference (SAD)) between blocks which can eliminate an impossible candidate block much earlier than a conventional partial distortion elimination (PDE) scheme. The basic idea of the proposed scheme is based on predicting the total SAD of a candidate block using its partial SAD. In particular, in order to improve prediction accuracy and computational efficiency, a sub-sample based block matching and a selective pixel-based approaches are employed. In order to evaluate the proposed scheme, several baseline approaches are described and compared. The experimental results show that the proposed algorithm can reduce the computations by about 44% for motion estimation at the cost of 0.0005 dB quality degradation versus the general PDE algorithm.

• 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.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.23-25
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• 2007

The partial distortion elimination (PDE) scheme is used to decrease the sum of absolute difference (SAD) computational complexity, since the SAD calculation has been taken much potion of the video compression. In motion estimation (ME) based on PDE, it is ideal that the initial value of SAD in summing performance has large value. The traditional scan order methods have many operation time and high operational complexity because these adopted the division or multiplication. In this paper, we introduce the new scan order and search order by using only adder. We define the average value which is called to rough average value (RAVR). Which is to reduce the computational complexity and increase the operational speed and then we can obtain the improvement of SAD performance. And also this RAVR is used to decide the search order sequence, since the difference RAVR between the current block and candidate block is small then this candidate block has high probability to suitable candidate. Thus, our proposed algorithm combines above two main concepts and suffers the improving SAD performance and the easy hardware implementation methods.

• Progress in Superconductivity
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• v.4 no.2
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• pp.114-120
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• 2003

We employed a method eliminating a temporally partial principal component (PC) of multichannel-recorded neuromagnetic fields for excluding spatially correlated noises from event-evoked signals. The noises in magnetoencephalography (MEG) are considered to be mainly spontaneous neuromagnetic fields which are spatially correlated. In conventional MEG experiments, the amplitude of the spontaneous neuromagnetic field is much lager than that of the evoked signal and the synchronized characteristics of the correlated rhythmic noise makes it possible for us to extract the correlation noises from the evoked signal by means of the general PC analysis. However, the whole-time PC of the fields still contains a little projection component of the evoked signal and the elimination of the PC results in the distortion of the evoked signal. Especially, the distortion will not be negligible when the amplitude of the evoked signal is relatively large or when the evoked signals have a spatially-asymmetrical distribution which does not cancel out the corresponding elements of the covariance matrix. In the period of prestimulus, there are only the spontaneous fields and we can find the pure noise PC that is not including the evoked signal. Besides that, we propose a method, called the extended temporal decorrelation method (ETDM), to suppress the distortion of the noise PC from remanent evoked signal components. In this study, we applied the Partial Principal component elimination method (PPCE) and ETDM to simulated signals and the auditory evoked signals that had been obtained with our homemade 37-channel magnetometer-based SQUID system. We demonstrate here that PPCE and ETDM reduce the number of epochs required in averaging to about half of that required in conventional averaging.

• 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 Multimedia Society
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• v.8 no.8
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• pp.1080-1087
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• 2005

Significant computations for full search (FS) motion estimation have been a big obstacle in real-time video coding and recent MPEG-4 AVC (advanced video coding) standard requires much more computations than conventional MPEG-2 for motion estimation. To reduce an amount of computation of full search (FS) algorithm for fast motion estimation, we propose a new and fast matching algorithm without any degradation of predicted images like the conventional FS. The computational reduction without any degradation in predicted image comes from fast elimination of impossible candidate motion vectors. We obtain faster elimination of inappropriate motion vectors using efficient matching units from localization of complex area in image data and dithering order based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination (PDE) algorithm, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.