• 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.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.177-180
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• 2001

This paper presents a new fast motion estimation algorithm for video coding. This method classifies blocks in a frame into moving blocks and background blocks, and then searches the best-matched blocks for only moving blocks. Experimental results show the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.925-931
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• 2008

In video coding standard H.264/AVC, variable block size mode algorithm improves compression efficiency but has need of a large amount of computation for various block modes and mode decision. Meanwhile, decided inter block modes depend on the complexity of a block image, and then the more complex a macroblock is, the smaller its block size is. This paper proposes fast inter block mode decision algorithm. It limits valid block modes to the block modes with a great chance for decision using the image complexity and carries out motion estimation rate-distortion optimization with only the valid block modes. In addition to that, it applies fast motion estimation PDE to the valid block modes with only the $16{\times}16$ block mode. The reference software JM 9.5 was executed to estimate the proposed algorithm's performance. The simulation results showed that the proposed algorithm could save about 24.12% of the averaged motion estimation time while keeping the image quality and the bit rate to be -0.02dB and -0.12% on the average, respectively.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1-4
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• 1996

It is difficult that a non-translational motion in a block is estimated by the block matching algorithm (BMA). In this paper, a nodal-displacement-based deformation model is used for this reason. This model assumes that a selected number of control nodes move freely in a block and that displacement of any interior point can be interpolated from nodal displacements. As a special case with a single node this model is equivalent to a translational model. And this model can represent more complex deformation using more nodes. We used an iterative gradient based search algorithm to estimate nodal displacement. Each iteration involves the solution of a simple linear equation. This method is called the deformable block matching algorithm (DBMA).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.258-263
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• 2006

Each pixel in a matching block does not equally contribute to block matching and the matching error is greatly affected by image complexity. On the basis of the facts, this paper proposes a fast motion estimation algorithm using some sub-blocks selected by the image complexity. The proposed algorithm divides a matching block into 16 sub-blocks, computes the image complexity in every sub-block, executes partial block matching using some sub-blocks with large complexity, and detects a motion vector. The simulation results show that the proposed algorithm brings about negligible image degradation, but can reduce a large amount of computation in comparison with conventional algorithms.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.94-101
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• 2002

In this paper, we propose a motion estimation algorithm for the discontinuity blocks. The algorithm uses sub-SAD value (i.e. the sum of absolute difference for a quarter of a block) to identify the discontinuity region, and produces additional motion vectors for these sub-blocks if necessary. We show with experimental results that, in comparison with some conventional motion estimation algorithms, the proposed algorithm achieves quality enhancement for the sequences with discontinuity blocks, and also shows the same computational quantity as to normal algorithms for sequences with less discontinuity.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.987-992
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• 2004

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 the improved diamond search pattern using an motion vector prediction candidate search point by the predicted motion information from the same block of the previous frame. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improves as high as high as 14~24% in terms of average number of search point per motion vector estimation and improved about 0.02~0.37dB on an average except the full search(FS) algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.8
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• pp.966-974
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• 1999

완전 탐색 블록 정합 알고리즘(FBMA)은 다양한 움직임 추정 알고리즘 중 최상의 움직임 추정을 할 수 있으나, 방대한 계산량이 실시간 처리의 적용에 장애 요소이다. 본 논문에서는 완전 탐색 블록 정합 알고리즘에 비해 더 낮은 계산량과 유사한 화질을 가지는 새로운 고속 움직임 추정 알고리즘을 제안한다. 제안한 방법에서는 공간적인 상관성을 이용함으로써 적절한 탐색 영역의 크기를 예측할 수 있다. 현재 블록의 움직임 추정을 위하여 이웃 블록이 가지고 있는 움직임과 탐색 영역의 크기를 이용하여 현재 블록의 탐색 영역을 적응적으로 변화시키는 방법이다. 이 예측값으로 현재 블록의 탐색 영역 크기를 결정한 후, FBMA와 같이 이 영역 안의 모든 화소점들에 대하여 현재 블록을 정합하여 움직임 벡터를 추정한다. 컴퓨터 모의 실험 결과 계산량 측면에서 제안 방법이 완전 탐색 블록 정합 알고리즘보다 50%정도 감소하였으며, PSNR 측면에서는 0.08dB에서 1.29dB 정도 감소하는 좋은 결과를 얻었다.Abstract Full search block-matching algorithm (FBMA) was shown to be able to produce the best motion compensated images among various motion estimation algorithms. However, huge computational load inhibits its applicability in real applications. A new motion estimation algorithm with lower computational complexity and good image quality when compared to the FBMA will be presented in this paper. In the proposed method, The appropriate search area can be predicted by using the temporal correlation between neighbouring blocks. For motion estimation of the current block, it is the method changing adjustably search area of current block by using motion and search area size of the neighbouring block. After deciding search area size of the current block with this predicted value, we estimate motion vector that matching current block like the FBMA for every pixel in this area. By the computer simulation the computation amount of the proposed method can be greatly decreased about 50% than that of the FBMA and the good result of the PSNR can be attained.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.