Algorithm and Architecture Co-Design of Hardware-Oriented, Modified Diamond Search for Fast Motion Estimation in H.264/AVC

Ogunfunmi, Tokunbo

doi:10.1109/tcsvt.2011.2133990

Cited by 60 publications

(22 citation statements)

References 15 publications

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“…Architecture presented in [25] is configurable for mapping five different BMAs (BBGDS, DS, CDS, HEXBS, and TSS). Hardware oriented Modified Diamond Search (HMDS) [26] use two shapes having 17 and 13 search points and provides better PSNR for center biased low motion sequences.…”

Section: Block Matching Methods and Algorithmsmentioning

confidence: 99%

Multi Point Search Pattern for Fast Search Motion Estimation of High Resolution Video Coding

Shah¹,

Dalal

Prajapati³

2015

IJIGSP

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Abstract-Block matching algorithm (BMA) based motion estimation (ME) is most accepted method for removal of temporal redundancy between frames in video coding. With recent advancement in resolution of video, the need of search pattern covering most of macroblocks within search area in frame is increasing. Existing search patterns are tiny and take plenty of time to reach at edge or corner of the search window. With aim of covering nearly every probable candidate macroblocks in all direction and to speed up the search process, multipoint search patterns are presented in this paper. Initial candidate macroblocks are chosen on grid of 12x12 and then search progresses like traditional diamond or hexagon search. Due to multipoint, chances of trapping in incorrect direction is very less and method can exhibit better quality of encoding with optimum number of search points.Index Terms-Motion Estimation, Fast search block matching algorithm, Multi point search, H.265, HD video sequences.

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Section: Block Matching Methods and Algorithmsmentioning

confidence: 99%

Multi Point Search Pattern for Fast Search Motion Estimation of High Resolution Video Coding

Shah¹,

Dalal

Prajapati³

2015

IJIGSP

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“…Hence, most ME architectures have 256 PEs. The number of PEs in [40] and [41] is only 72 and 64, respectively, since [40] uses a 4:1 subsample method and [41] supports only the CIF resolution. To support real-time processing at a lower frequency, the number of PEs in [38] is 512, which is twice that of the others [9], [39], [42].…”

Section: Performance Comparisonsmentioning

confidence: 99%

MESIP: A Configurable and Data Reusable Motion Estimation Specific Instruction-Set Processor

Kim

Sunwoo

2013

IEEE Trans. Circuits Syst. Video Technol.

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This paper proposes a new motion estimation (ME)-specific instruction-set processor (MESIP) with a novel search scan order with high data reusability, to efficiently implement various advanced ME algorithms. The proposed ME-specific instructions can be selectively used for ME algorithms. The novel data-reusing search scan order, called center biased search scan (CBSS), exploits the symmetry of the search pattern to reduce redundant data loading on MESIP by about 26.9% and 16.1% compared with raster scan and snake scan, respectively. MESIP has been implemented with IBM's 90-nm CMOS technology and has 203K gates excluding memory. Simulation results show that the proposed MESIP can reduce the number of required instructions by up to 18.9% compared with existing ME processors. Moreover, MESIP achieves comparable performance even with ME ASICs and hence may be quite suitable for a low-power and high-performance ME implementation.Index Terms-Application-specific instruction-set processor (ASIP), configurable architecture, low-power design, motion estimation/motion compensation (ME/MC), search scan order.

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“…A possible classification of these fast search motion estimation algorithms into the following categories: reduction in search positions [1][2][3][4][5][6][7][8][9], predictive search [10][11][12][13][14], search pattern switching [15], [16], multi-resolution search [17][18][19][20] and Fractional-Pixel Interpolation [21][22]. Existing fast search motion estimation algorithms use one or a combination of these categories.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Block Matching Algorithms for Video Coding

Paramkusam¹,

Arun²

2017

IJECE

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Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades, hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality. Keyword:Block INTRODUCTIONThe main objective of block matching algorithms is to determine the direction and magnitude of motion (motion vector) for a macroblock in the current frame relative to the best matched candidate block in the reference frame. The search for the best matching candidate block may be carried out by comparing the macroblock in the current frame with some or all the possible candidate blocks in a search window. FullSearch (FS) is an exhaustive search algorithm and it is the simplest method to find the optimal motion vectors for each macroblock. It determines the best matched candidate block through calculating the Sum of Absolute Difference (SAD) for all candidate blocks in the search window. Although Full-Search can obtain the global optimal result, it has very intensive computations.To reduce the complexity of Full-Search, several fast search motion estimation algorithms have been proposed at the price of slightly impaired Peak Signal-to-Noise Ratio (PSNR) performance. A possible classification of these fast search motion estimation algorithms into the following categories: reduction in search positions [1][2][3][4][5][6][7][8][9], predictive search [10][11][12][13][14], search pattern switching [15], [16], multi-resolution search [17][18][19][20] and Fractional-Pixel Interpolation [21][22]. Existing fast search motion estimation algorithms use one or a combination of these categories. A popular example is the three-step search (TSS) algorithm [1]. However, its uniformly spaced search pattern is not well matched to most real-world video sequences in which the motion vector distribution is non-uniformly biased toward the zero vector. Such an observation inspired the new three-step search (NTSS) which has a centre-biased search pattern and supports a halfwaystop technique [2]. The centre-biased NTSS algorithm is an improved version of TSS, tends to achieve much superior performance with fewer number of search points on average. The search pattern has an important influence on speed and distortion performance in block motion estimation.In TSS and NTSS algorithms square-shaped search patterns of different sizes are employed. The Diamond search (DS) algorithm adopts a diamond-shaped search pattern [3], which is more efficient than

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Algorithm and Architecture Co-Design of Hardware-Oriented, Modified Diamond Search for Fast Motion Estimation in H.264/AVC

Cited by 60 publications

References 15 publications

Multi Point Search Pattern for Fast Search Motion Estimation of High Resolution Video Coding

Multi Point Search Pattern for Fast Search Motion Estimation of High Resolution Video Coding

MESIP: A Configurable and Data Reusable Motion Estimation Specific Instruction-Set Processor

A Survey on Block Matching Algorithms for Video Coding

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