Uluğ Bayazıt, William A. Pearlman · 1997
The Rate Constrained Block Matching Algorithm, (RC-BMA), introduced in this paper jointly minimizes DFD (Displaced Frame Difference) variance and entropy or conditional entropy of motion vectors for determining the motion vectors in low rate video coding applications where the contribution of the motion vector rate to the overall coding rate might be significant. The motion vector rate vs. DFD variance performance of RC-BMA employing size KxK blocks is shown to be superior to that of the conventional Minimum Distortion Block Matching Algorithm (MD-BMA) employing size 2Kx2K blocks. Constraining of the entropy or conditional entropy of motion vectors in RC-BMA results in smoother and more organized motion vector fields with respect to those output by MD-BMA. The motion vector rate of RC-BMA can also be fine tuned to a desired level for each frame by adjusting a single parameter. Keywords : Motion estimation, block matching, vector quantization, entropy constraint, video coding 1 Introd...
Cited by 0
Shu Guo, Chih-Yuan Hsu · Journal of Electronic Imaging · 2013
Block-matching motion estimation (ME) is a principal process for most existing video compression standards, but it has a significant impact on computation overhead. An efficient block-matching algorithm is proposed for ME. The proposed algorithm consists of three effective steps: (1) apply the full search (FS) algorithm to construct a polynomial interpolation model from the group with four skipping frames to determine near-optimal global motion vector (MV) for the initial search point, (2) perform an adaptive search pattern in the interpolation step to refine the MV and (3) use the half-way stop technique to reduce search points. Experimental results show that the proposed algorithm achieves a maximum speed-up factor of 366.47 with only 0.52% peak signal-to-noise ratio (PSNR) degradation in comparison with the FS algorithm.
Cited by 1
Bulletin of Miscellaneous Information (Royal Gardens Kew)
With the recent advances in video technology, there is an increasing need for a more reliable, efficient and robust generic framework for video processing and its analysis. In this regard the Motion estimation has for many years demanding area of research because of its diversity of use in real-time applications. Motion estimation using block matching algorithm is used in many applications in video processing. This paper presents a review of motion estimation based on block matching algorithm and also includes analytical study of fixed and variable block matching algorithms
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Feng Ju, Kwok‐Tung Lo, H. Mehrpour et al. · IEE Proceedings - Vision Image and Signal Processing · 1998
A simple adaptive block matching algorithm for video coding is presented. In the proposed algorithm, a matching criterion called bit-plane matching is proposed to sort out a number of blocks with unlikely directive information to the test block from the search window. An adaptive searching method is developed to further improve the computational effectiveness of the system. In this searching method the search origin, search range and pixel subsampling ratio can be adjusted according to the motion content of the block. Simulation results show that the proposed algorithm achieves similar MSE performance to the full-search method and about 92–95% savings in computation.
Cited by 6
Chen, Zong · Zenodo (CERN European Organization for Nuclear Research) · 2009
Motion estimation is a key problem in video processing and computer vision. Optical flow motion estimation can achieve high estimation accuracy when motion vector is small. Three-step search algorithm can handle large motion vector but not very accurate. A joint algorithm was proposed in this paper to achieve high estimation accuracy disregarding whether the motion vector is small or large, and keep the computation cost much lower than full search.
Cited by 0Open access
Haifeng Wang, Qingshan Liu, Hanqing Lu · 2015
In H.264, the variable-size block motion estimation is the most time-consuming component. To reduce the complexity of motion estimation, we proposed a fast “bottom-up ” variable-size block-matching algorithm based on macro-mode prediction and motion vector prediction. The macro-mode prediction method is used to accelerate the mode selection process. During the prediction process, the macro block is split into four sub-blocks to avoid introducing any loss to the prediction precision. The motion vector prediction method is based on the correspondence between motion vectors of consecutive frames. Different from the traditional fast variable-size block matching algorithms, this motion vector prediction method is used to find motion vectors for candidate sets to guide the merge procedure. Experiments show its promising performance.
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V.K. Ananthashayana, Pushpa.M.K · Zenodo (CERN European Organization for Nuclear Research) · 2009
In this paper a new Joint Adaptive Block Matching Search (JABMS) algorithm is proposed to generate motion vector and search a best match macro block by classifying the motion vector movement based on prediction error. Diamond Search (DS) algorithm generates high estimation accuracy when motion vector is small and Adaptive Rood Pattern Search (ARPS) algorithm can handle large motion vector but is not very accurate. The proposed JABMS algorithm which is capable of considering both small and large motions gives improved estimation accuracy and the computational cost is reduced by 15.2 times compared with Exhaustive Search (ES) algorithm and is 1.3 times less compared with Diamond search algorithm.
Cited by 0Open access
Feng Ya Lin, Yang Xiao Kang, Yu Song Yu · 1999
Block-matching motion estimation plays an important role in video coding. In this paper, we present an adaptive block-matching algorithm, which determines the candidate motion vectors and a dynamic search window based on the spatial and temporal neighbor blocks. According to the mean absolute error (MAE) based on these motion vectors, stop search, 3/spl times/3 neighbor window search and modified 3SS search in the dynamic window is applied adaptively. This method can significantly reduce search time while the performance is still maintained. Simulation results show the performance of this algorithm is very similar to that of the full search algorithm (FSA) and the computation complexity is smaller than that of 3SS and 4SS.
Cited by 1
Chun‐Hung Lin, Ja‐Ling Wu · 2002
Genetic algorithms (GAs) recently have been successfully applied to perform block-based motion estimation. It is shown that the performance of the GA-based motion estimation algorithms nearly approaches that of the full search algorithm (FSA). However, the computational complexity of the existing GA-based algorithms is too high to be used in practice. In this paper, a lightweight genetic search algorithm (LGSA) is proposed. It can be seen from the simulation results that the performance of the proposed LGSA is not only as good as that of the FSA, but the computational complexity is also much lower than that of the FSA and the other existing genetic motion estimation algorithms.
Cited by 16
Joonkyung Kim, Rae‐Hong Park · Electronics Letters · 1989
A fast block matching algorithm using integral projections for the estimation of motion vectors is proposed. In the calculation of the cost function, the proposed algorithm using integral projections as features can reduce the motion estimation computations by a factor of 3 by converting the operations of two-dimensional arrays into those of onedimensional arrays. Also, the proposed method is not sensitive to additive noise. Simulation results based on the sequence of original image and the sequences of noisy image with different standard deviation are presented.
Cited by 15
Florin Alexa, Zoran Bojković · 2002
We describe a new block matching algorithm (BMA) for motion estimation that takes into account the mean absolute-difference (MAD) criteria. The main functions of the BMA are analysed, too. To improve the performance of the estimation we increased the probability to find the real block displacement. The experimental results show that the proposed algorithm is very close to the full search algorithm in terms of mean square error (MSE).
Cited by 0
S. M. Reza Soroushmehr, Shadrokh Samavi · Conference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
In this paper a modified version of the predicted vector spectral search algorithm (PVSSA) is presented. The proposed method adaptively determines the search area for motion estimation. The maximum number of search points for finding the best matched block is lower than that of the PVSSA. Although the proposed algorithm is similar to the PVSSA in terms of regularity, it has lower computational complexity. To find the search area the temporal and spatial correlations among the motion vectors of the image blocks are exploited. Based on this, a matched block is chosen from a rectangular area that the prediction vectors set out. We have evaluated the algorithm through a comprehensive performance study that shows that the proposed algorithm achieves substantial speedup without quality loss for a wide range of video sequences, compared with other motion estimation techniques.
Cited by 10
2008
A fast and efficient hybrid block-matching motion estimation algorithm is proposed in this paper. The fact that motion characteristics are relatively stable in a GOP (group of pictures) is utilized to reduce the computation burden without quality degradation. For P-frames, a multi-resolution block-matching algorithm is used. At the coarsest level, edge information is used to reduce searching positions before an exhaustive search. At the finer levels, only the several candidates chosen at the upper level are verified. For Bframes, mean-absolute-error (MAE) is used not only for the matching criteria, but also for classifying the macroblocks with the motion information extracted from P-frames. Concurrently, the search window size is adjusted using the contribution of different motion range to the improvement of the picture quality with motion compensation. When the decoded I-frame and P-frames are used as the reference, experimental results show that reconstructed digital frames have even better quality than the full search algorithm in terms of PSNR, under MPEG-1 coding environment. 1.
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Chia Ming Wu, Jen Yi Huang · Applied Mechanics and Materials · 2016
Motion estimation has been the most key role on video processing. It is usually applied to block matching algorithm for choosing the best motion vector. The two adjacent images are searched to find the displacement of the same object in the video image. Many fast motion vector block matching algorithms are proposed, and they achieve the efficiency of motion compensation and video compression. In our paper, we propose a new algorithm that is based on ARPS. The experimental results show that the PSNR of the proposed method is better than that of other block matching methods on many kinds of video.
Cited by 6Open access
Xinghua Sun, Jin Guo-ying, Mei Huang et al. · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Integral image as an intermediate image representation can be used to calculate the sum of gray level in rectangle quickly, based on which this paper presents a novel partial matching error function based on sub block mean. The optimal sub block division is a key to the matching error function based on sub block mean and is determined to be 4 under the hierarchical block matching. Experiments show that the matching error function based on sub block mean is superior to both the full matching error function and the matching error function based on sub sampling in terms of the motion estimation quality and speed. The matching error function based on sub block mean with the content sub block division guarantees the almost same wasting time to the different matching images, which is very suitable for the real-time applications such as video compression.
Cited by 1
Mohammad Mahdi Azadfar · 2015
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Vasily G. Moshnyaga · 1999
A new adaptive algorithm for the block matching motion estimation is presented. The algorithm works in the full-search fashion but unlike the FSBMA it adjusts the number of computations dynamically to picture variation. Due to incorporated mechanism of data-driven thresholding, the proposed approach performs as four times as less operations compared to the FSBMA while maintaining the same quality of results. Its hardware implementation is simple and compact. A supportive hardware design as well as simulation results on benchmarks are outlined.
Cited by 4
Yan Yang, Li Ma · 2012 4th Electronic System-Integration Technology Conference · 2012
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송우진 · Open Access System for Information Sharing (Pohang University of Science and Technology) · 2018
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Ngai Li, Chun-Man Mak, Wai-Kuen Cham · Lecture notes in computer science · 2006
Cited by 3