• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.4
• /
• pp.104-115
• /
• 1993

The motion compensated coding (MCC) technique, which exploits the temporal redundancies in the moving images with the motion estimation technique,is one of the most popular techniques currently used. Recently, a variable block size(VBS) motion estimation scheme has been utilized to improve the performance of the motion compensted coding. This scheme allows large blocks to the used when smaller blocks provide little gain, saving rates for areas containing more complex motion. Hence, a new VBS motion estimation scheme with a hierarchical structure is proposed in this paper, in order to combine the motion vector coding technique efficiently. Topmost level motion vector, which is obtained by the gain/cost motion estimation technique with selective motion prediction method, is always transmitted. Thus, the hierarchical VBS motion estimation scheme can efficiently exploit the redundancies among neighboring motion vectors, providing an efficient motion vector encoding scheme. Also, a restricted search with respect to the topmost level motion vector enables more flexible and efficient motion estimation for the remaining lower level blocks. Computer simulations on the high resolution image sequence show that, the VBS motion estimation scheme provides a performance improvement of 0.6~0.7 dB, in terms of PSNR, compared to the fixed block size motion estimation scheme.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.749-752
• /
• 2008

Various Motion Estimation (ME) algorithms have been proposed since ME requires large computational complexity. The proposed algorithm employs Enhanced Cross Search Pattern (ECSP) using motion vector of neighbor-blocks to search the motion vector. The experimental results show that proposed algorithm reduces the search point up to 35% compared to conventional methods.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.639-642
• /
• 2005

Motion Estimation(ME) is an important part of video compression, because it requires a large amount of computation. Half-pixel and quarter-pixel motion estimation allows high video compression rates but it also has high computation complexity. In this paper we suggest a new and efficient motion estimation algorithm for half-pixel and quarter-pixel motion estimation using SAD values. In the method, an integer-pixel motion vector is found and then only three neighboring points of the integer-pixel motion vector is evaluated to find the half-pixel motion vector. The quarter-pixel motion vector is also found by using a similar method. Experimental results of our method shows 20% reduction in computation time, when compared with those of a conventional method, while producing same quality motion vectors.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.2C
• /
• pp.141-146
• /
• 2003

In this paper, we propose an adaptive search range decision algorithm for motion vector estimation in video coding. The performance of general motion estimation method in video coding mechanism is evaluated with respect to the motion vector accuracy and the complexity, which is trade-off. The proposed algorithm that plays as a role of pre-processing for motion vector estimation determines the motion search range by the local statistics of motion vector of neighboring blocks, resulting in more than 60(%) reduction of the computational cost without the loss of visual quality. Experimental results show the capability of the proposed algorithm.

• Journal of Broadcast Engineering
• /
• v.20 no.6
• /
• pp.880-887
• /
• 2015

In this paper, frame rate up conversion (FRUC) algorithm considering the direction and magnitude of identical motion vectors is proposed. extended bilateral motion estimation (EBME) has higher complexity than bilateral motion estimation (BME). By using average magnitude of motion vector with x and y direction respectively, dynamic frame and static frame are decided. We reduce complexity to decide EBME. also, After we compare the direction and magnitude of identical motion vectors, We reduce complexity to decide motion vector smoothing(MVS). Experimental results show that this proposed algorithm has fast computation and better peak singnal to noise ratio(PSNR) results compared with EBME.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.3
• /
• pp.77-88
• /
• 1995

It is assumed in the block matching algorithm(BMA) that all the pels in a block have a same motion vector. Then, the motion vector of a block in the BMA is matched to only one or none of the objects in the worst case if objects in a block have different motion vectors. This is apparent in the motion estimation using the fast BMA which has the effect of reducing the computation time and hardware complexity, compared to the full search BMA. Although the motion vector in the motion estimation using small block size is accurate, the increased number of bits is required to represent motion vectors. In this paper, new motion vector segmentation with less additional information and hardware complexity than the conventional method is proposed. In the proposed method, a motion vector is derived from the block for motion vector segmentation and another motion vector is extracted from four neighboring blocks to consiture a motion vector pair. For the accurate motion vector of each subblock, the motion vector is assigned to each subblock by mean squared error measure. And the overlapped motion compensation using window is also applied to reduce displaced frame difference.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.6
• /
• pp.64-72
• /
• 1996

In this paper, we propose predictive motion estimatin algorithm which can predict motion without additional side information considering spatio-tempral correlatio of motion vector. This method performs motion prediction of current block using correlation of the motion vector for two spatially adjacent blocks and a temporally adjacent block. Form predicted motion, the position of searhc area is determined. Then in this searhc area, we estimate motion vector of current block using block matching algoirthm. Considering spatial an temporal correlation of motion vector, the proposed method can predict motion precisely much more. Especially when the motion of objects is rapid, this method can estimate motion more precisely without reducing block size or increasing search area. Futhrmore, the proposed method has computation time the same as conventional block matching algorithm. And as it predicts motion from adjacent blocks, it does not require additional side information for adjacent block. Computer simulation results show that motion estimation of proposed method is more precise than that of conventioanl method.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.8
• /
• pp.602-605
• /
• 2004

A novel motion vector re-estimation technique for transcoding into lower spatial resolution is proposed. This technique is based on the fact that the block matching error is proportional to the complexity of the reference block with Taylor series expansion. It is shown that the motion vectors re-estimated by the proposed method are closer to optimal ones and offer better quality than those of previous techniques.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2017.06a
• /
• pp.66-69
• /
• 2017

본 논문에서는 프레임율 향상 기법 (Frame Rate Up-Conversion, FRUC)에 사용되는 새로운 움직임 예측(motion estimation)알고리즘을 제시한다. 제안된 알고리즘은 단 방향 움직임 예측(unilateral motion estimation)에 의해 순방향 및 역방향의 움직임 벡터(motion vector)를 독립적으로 추정한다. 움직임 벡터를 찾은 후, weighted motion vector smoothing(WMVS)가 적용된다. 다음으로, 보간 프레임 (interpolated frame)의 관점에서 현재 블록의 인접 블록들의 모션 벡터들을 후보들로 사용하여 현재 블록과 가장 잘 일치하는 움직임 벡터를 찾는다. 그 후, 선택된 움직임 벡터를 현재 블록의 유도 움직임 벡터 (guidance motion vector)로 정한다. 그런 다음 motion vector shifting error 를 없애기 위해 motion vector refinement (MVR)가 진행된다. 마지막 단계에서는 각 움직임 벡터의 신뢰도를 계산하여 순방향 및 역방향 움직임 벡터 중 최종 움직임 벡터를 선택한다.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.2
• /
• pp.59-68
• /
• 1993

The motion vector estimation and motion boundary detection have been briskly studied since they are an important clue for analysis of object structure and 3-d motion. The purpose of this researches is more exact estimation, but there are two main causes to make inaccurate. The one is the erroneous measurement of gradients in brightness values and the other is the blurring of motion boundries which is caused by the smoothness constraint. In this paper, we analyze the gradient measurement error of conventional methods and propose new technique based on it. When the proposed method is applied to the motion boundary detection in Schunck and motion vector estimation in Horn & Schunck, it is shown to have much better performance than conventional method is some artificial and real image sequences.