• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1097-1100
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• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.991-999
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• 2010

In this paper, we propose a fast motion estimation algorithm for video encoding. Conventional fast motion estimation algorithms have a serious problem of low prediction quality in some frames. However, full search based fast algorithms have low computational reduction ratio. In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution probability of motion vectors and adaptive search patterns and block matching criteria. By taking different search patterns and error criteria of block matching according to distribution probability of motion vectors, we can reduces only unnecessary computations efficiently. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2 or MPEG-4 AVC standards.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.808-815
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• 2013

In this paper, we propose a novel fast and low-complexity Motion Estimation (ME) algorithm for Ultra High Definition (UHD) High Efficiency Video Coding (HEVC). Motion estimation occupies 77~81% of the amount of computation in HEVC. After all, the main key of video codec implementation is to find a fast and low-complexity motion estimation algorithm and architecture. We analyze the previous motion estimation algorithms and propose three optimal algorithm to reduce the computation proportion for HEVC. The proposed algorithm uses only 0.36% of the amount of operations compared to full search algorithm while maintaining compression performance with slight loss of 1.1%.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.84-90
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• 2019

Tremendous computation of full search or lossless motion estimation algorithms for video coding has led development of many fast motion estimation algorithms. We still need proper control of computation and prediction quality. In the paper, we suggest an algorithm that reduces computation effectively and controls computational amount and prediction quality, while keeping prediction quality as almost the same as that of the full search. The proposed algorithm uses multiple thresholds for partial block sum and times of counting unchanged minimum position for each step. It also calculates the partial block matching error, removes impossible candidates early, implements fast motion estimation by comparing times of keeping the position of minimum error for each step, and controls prediction quality and computation easily by adjusting the thresholds. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.211-214
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• 2001

This paper presents an efficient fast motion estimation algorithm and image segmentation method for low bit-rate coding. First, with region split information, the algorithm splits the image having homogeneous and semantic regions like face and semantic regions in image. Then, in these regions, We find the motion vector using adaptive search window adjustment. Additionally, with this new segment based fast motion estimation, we reduce blocking artifacts by intensively coding our interesting region(face or arm) in input image. The simulation results show the improvement in coding performance and image quality.

• 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 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.

• ETRI Journal
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• v.31 no.6
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• pp.784-794
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• 2009

We present a full HD (1080p) H.264/AVC High Profile hardware encoder based on fast motion estimation (ME). Most processing cycles are occupied with ME and use external memory access to fetch samples, which degrades the performance of the encoder. A novel approach to fast ME which uses shared multibank memory can solve these problems. The proposed pixel subsampling ME algorithm is suitable for fast motion vector searches for high-quality resolution images. The proposed algorithm achieves an 87.5% reduction of computational complexity compared with the full search algorithm in the JM reference software, while sustaining the video quality without any conspicuous PSNR loss. The usage amount of shared multibank memory between the coarse ME and fine ME blocks is 93.6%, which saves external memory access cycles and speeds up ME. It is feasible to perform the algorithm at a 270 MHz clock speed for 30 frame/s real-time full HD encoding. Its total gate count is 872k, and internal SRAM size is 41.8 kB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.807-821
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• 1996

In this paper, we proposed a nonlinear hierarchical mtion estimation method. Generally, the conventional hierarchical motion estimation methods have been proposed for fast convergence and detection of large motions. But they have a common drawback that large error in motion estimation is propapated across motion discontinuities. This artifiact is due to the constriaint of motion continuity and the linear interpolation of motion vectors between hierarchical levels. In this paper, we propose an effective hierarchical motion estimation mechod that is robust to motion discontinuities. The proposed algorithm is based on the decomposition of the functional domain for optimizing the intra-level motion estimation functional. Also, we propose an inter-level nonlinear motion estimation equation rather than using the conventional linearprojection scheme of motion field. computer simulations with several test sequences show tht the proposed algorithm performs better than several conventional methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.402-410
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• 2013

In this paper, we propose a new fast block matching algorithm for block matching using the temporal and spatially correlation of the video sequence and local statistics of neighboring motion vectors. Since the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vectors of neighboring blocks around the same block of the previous frame and the current frame and the predictor candidate point on each division region by binary-tree structure. Experimental results show that the proposed algorithm has the capability to dramatically reduce the search points and computing cost for motion estimation, comparing to fast FS(full search) motion estimation and other fast motion estimation.