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Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
Fast block motion estimation with 8 bit partial sums using SIMD architecture
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Fast block motion estimation with 8 bit partial sums using SIMD architecture

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  • 1. Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMDArchitecturesPresented by:•Ahmed Abdel-Hafeez•Ahmed El-Bohy•Ahmed Emam•Ahmed KandilSupervised by/Presented to:Pf.Dr. Attalah HashaadPublished by: Chunjiang J. Duanmu et. al.Published in August 2007.
  • 2. Outline• Abstract.• Introduction.• 8-bit partial sums.• Multilevel 8-bit partial sums.• Computational complexity.• Simulation Results.• Conclusion.2ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 3. Abstract• Fast block motion estimation algorithms are needed for real-timeimplementations of video coding standards due to the high computationalcomplexity of the full-search algorithm for block motion estimation.• In this paper, an algorithm using 8-bit partial sums of 16 luminance valuesfor a fast block motion estimation is proposed. The technique of using thepartial sums is employed to reduce the computational complexity of notonly the full search algorithm but also some of the fast block motionestimation algorithms while maintaining their accuracy.• Furthermore, it is shown that the byte-type data-parallelism on an SIMDarchitecture can be utilized to access and process these partial sumsconcurrently to accelerate the process of motion estimation.• Simulation results are presented to demonstrate that the use of thepartial sums can accelerate the execution of the full-search and anothersearch algorithms on an SIMD architecture significantly.3ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 4. 4Introduction- - ApplicationsARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slideBasics
  • 5. Chronological Table of Video Coding StandardsThe objective of video coding is to compress moving imagesH.261(1990)MPEG-1(1993)H.263(1995/96) H.263+(1997/98)H.263++(2000)H.264( MPEG-4Part 10 )(2002)MPEG-4 v1(1998/99)MPEG-4 v2(1999/00)MPEG-4 v3(2001)1990 1992 1994 1996 1998 2000 2002 2003MPEG-2(H.262)(1994/95)ISO/IECMPEGITU-TVCEG5
  • 6. Introduction-Basics- Video6Frame 1 Frame 2 Frame 3 Frame 4Luminance (Y) : Describes the brightness of the pixel.Chrominance (CbCr) : Describes the color of the pixel.FrameARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 7. Introduction-Basics- Video DataDrawback• An uncompressed video data is big in size.– This is due to data redundancy, there are twogeneral types of data redundancy in a video:7Spatial redundancyIn a frame, adjacent pixels areusually correlated. e.g. - The grass isgreen in the background of a frame.Frame 1 Frame 2 Frame 3 Frame 4Time based redundancyIn a video, adjacent frames areusually correlated. e.g. - The greenbackground is persisting frame afterframe.ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 8. • Predict current frame based on previously codedframes• Types of coded frames:– I-frame – Intra-coded frame, coded independently of allother frames– P-frame – Predictively coded frame, coded based onpreviously coded frame– B-frame – Bi-directionally predicted frame, coded based onboth previous and future coded framesIntroduction-Basics- VideoCompression8ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 9. Block Matching9ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 10. • What is Motion Estimation?– Predict current frame from previousframe– Determine the displacement of an objectin the video sequence– The amount of data to be coded can bereduced significantly if the previous frameis subtracted from the current frame.10Motion EstimationARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 11. Block Based Motion Estimation AlgorithmsTime-domain Algorithms Frequency-domain AlgorithmsMatching Algorithms Gradient Based AlgorithmsBlock-MatchingFeature-matchingPel-recursive Block-recursive Phase-correlation(DFT)Matchingin (DCT)domainMatchingin waveletdomainMesh Based Motion Estimation AlgorithmsMotion Estimation Classification11ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 12. Motion Estimation(ctd)12ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 13. Motion Estimation(ctd)13ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 14. 14Motion Estimation(ctd)ReferenceFrameCurrentFrameCurrent 16x16 BlockSearchWindowSum of AbsoluteDifference (SAD)ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 15. • CCF(Cross-Correlation Function)• MSE(Mean Square Error Function)• MAE(Mean Absolute Error)• SAD(Sum of Absolute Difference)• PDC(Pixel Difference Classification)• MAE(or MAD,SAD are commonly employed due to theirsimplicity in hardware implementation)Distortion Criterion for measuring distance betweenprevious block and search area block15ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 16. SAD(dx,dy) =(MVx, MVy) = min (dx,dy)ЄR2 SAD(dx,dy)1 11 |),(),(|NxxmNyynkk dyndxmInmISAD16ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 17. Search Algorithms17SearchAlgorithmsFASTMULTISTEP3SS 4SS HBS UDSEXHAUSTIVESE MSE VF PFGSEFULLARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 18. Search Algorithms(ctd)• There is a trade-off between the run time andthe accuracy.• Full search will be most accurate because ofexhaustive search, but will require more time• Fast search is faster but the accuracy will bereduced because of estimation algorithms.18ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 19. Full-Search19ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slidenot suitable for real time.
  • 20. •Simplest algorithm, but computationally most expensive20Exhaustive SearchARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 21. Three Step Search (3SSA)21ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 22. Three Step Search (3SSA)(ctd)22ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 23. Three Step Search (3SSA)(ctd)23ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 24. Three Step Search (3SSA)(ctd)24ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 25. 253SSA Block Matching►Three-Step Search (3SS)– 9 Points: Central point & its 8surroundings– Distance: w/2– Find the best match– Use previous best as center– Half distance, select 8 new– Repeat algorithm 3 times– Examines 25 points– Assumes a uniformdistribution of MV’s1111111 11232222222333 3 333ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 26. 4SSA26ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 27. Unrestricted center-bitiased DiamondSearch Algorithm (UDSA)27ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 28. Hexagon-Bitased search algorithm(HBSA)28ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 29. Problem Definition• The high computational requirement of the FullSearch (FS) algorithm does not allow it to work inreal time applications, despite its high accuracy.• Fast Block motion estimation algorithms havelower computational complexity, but loweraccuracy.• Since, fast block motion estimation are chosenfor real time applications  Hence in this papertoo.29ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 30. Aim• To improve the accuracy of some of the fastblock motion estimation techniques withoutincreasing the computational complexity.• To make best use of Single InstructionMultiple Data (SIMD) architecture and to takeadvantage of byte-type data-parallelism tofurther accelerate the execution of thealgorithms to achieve the main goal.30ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 31. Limitation• If the partial sums for an algorithm is morethan 8 bits for a reference block cannot beput, accessed, and manipulated in acontiguous memory space, since there arepartial sums of other reference blocks lying inbetween; due to this, a large number of CPUcycles are lost in manipulating these data. As aconsequence, these algorithms are notsuitable for SIMD implementations.31ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 32. Procedure• Devise a scheme that uses only 8 bit partialsum and discard as many SAD computationsas possible, without excluding the optimalmotion vector.– The proposed partial sums can not only be utilizedin the full-search algorithm as well as in some ofthe fast block motion-estimation algorithms.• Devise a scheme that generalises the previousscheme to multi-level case and optimallyutilise it.32ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 33. Partial Sums33268+ 483600Add the hundreds (200 + 400)Add the tens (60 +80) 140Add the ones (8 + 3)Add the partial sums(600 + 140 + 11)+ 11751ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 34. 8 Bit Partial Sums- Objective• The objective of this paper is to find newpartial sums of only eight bits, so that theycan be of the packed byte-type on an SIMDarchitecture.• In this way, eight additions or subtractions, forthe partial sums can be executed in one SIMDinstruction34ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 35. 8-bit Partial Sums012345678910111213141516 X 1635ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide∑(n)
  • 36. Lower Bound36ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slideusing
  • 37. Scheme One- Algorithm37ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide• Step 1) Initializationa) Compute all of the 8-bit partial sums ofsixteen luminance values for the currentframe and save them in a contiguousmemory space.b) Retrieve all the 8-bit partial sums of sixteenluminance values for the reference frame in asaved contiguous memory
  • 38. Scheme One- Algorithm(ctd)• Step 2) For every current block, execute the blockmotion-estimation process.– Step 2.1) Initialization38ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 39. Scheme One- Algorithm(ctd)– Step 2.2) Search• For (each search location of in a motion-estimation algorithm)39ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 40. 40Scheme One- Flow ChartARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 41. Multilevel 8-bit Partial Sums16 X 1641ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 42. Multi-level Visualisation
  • 43. Multi-level Visualisation
  • 44. Multi-level Visualisation (ctd)
  • 45. Multi-level Visualisation (ctd)
  • 46. Multi-level Visualisation (ctd)
  • 47. Multi-level Visualisation (ctd)
  • 48. Multi-level Visualisation (ctd
  • 49. Partial Sum PyramidPartial Sum Pyramid8 x 164 x 162 x 161 x 16Level 1 Level 2 Level 3 Level 449ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 50. 50Multilevel 8-bit Partial Sums- UpperBound (UB)ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide.
  • 51. Scheme Two Algorithm51ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide• Step 1) Initializationa) Compute all of the 8-bit partial sums of levelsone and four for the current frame and savethem in a contiguous memory space.b) Retrieve all of the 8-bit partial sums of levelsone and four for the reference frame in asaved contiguous memory space.
  • 52. Scheme Two Algorithm (ctd)52ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide• Step 2) For every current block, execute the blockmotion-estimation process.– Step 2.1) Initialization
  • 53. Scheme Two Algorithm (ctd)53– Step 2.2) Search• For (each search location of in a motion-estimation algorithm)
  • 54. Scheme Two- Flow Chart54
  • 55. Possible Conditions55ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slideCondition 1:Condition 2:Condition 3:Condition 4:
  • 56. Possible Combinations56ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 57. AVERAGEEXECUTION TIME(INMILLISECONDS)PERFRAME FORVARIOUSMETHODSResults57ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 58. Possible Combinations58ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 59. SIMD59ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 60. COMPUTATIONAL COMPLEXITY AND AVERAGENUMBER OF CPU CYCLES PER BLOCK USING FSA60ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 61. COMPUTATIONAL COMPLEXITY AND AVERAGENUMBER OF CPU CYCLES PER BLOCK USING SEA61ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 62. COMPUTATIONAL COMPLEXITY AND AVERAGENUMBER OF CPU CYCLES PER BLOCK USING 3SSA62ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 63. COMPUTATIONAL COMPLEXITY ANDAVERAGENUMBER OF CPU CYCLES PER BLOCK USING 4SSA63ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 64. COMPUTATIONAL COMPLEXITY AND AVERAGENUMBER OF CPU CYCLES PER BLOCK USING UDSA64ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 65. COMPUTATIONAL COMPLEXITY AND AVERAGENUMBER OF CPU CYCLES PER BLOCK USING HBSA65ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 66. THE PERCENTAGE OF SPEEDUP OFFERED BY SIMD IMPLEMENTATION FORA MOTION ESTIMATION ALGORITHM WITH SCHEME 2 INCORPORATED66ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 67. ConclusionIntroduced a new technique of 8 bit partialsum.The partial sums were used to make best useof SIMD architecture, and hence improvingthe speed of motion estimation algorithm.Since these partial sums have thecharacteristic of having only 8 bits, eight ofthem can be processed concurrently using asingle 64-bit SIMD register.67ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 68. Conclusion The notion of the 8-bit partial sums has then beenextended to the four-level case and shown that there are15 possible methods of utilizing these multilevel partialsums to accelerate the block motion-estimation algorithmswithout any loss of accuracy. The full-search algorithm has then been used to determineas to which one of these 15 methods would provide thelowest computational complexity in order for it to bechosen to accelerate various motion-estimation algorithms.68ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 69. Conclusion Extensive simulations have been carried out to findthe average number of CPU cycles needed per block forvarious algorithms incorporating the chosen method. These simulations have shown that the proposedscheme is capable of providing a substantial speed-upfor the various existing motion-estimation algorithmsthrough the reduction of their computationalcomplexities. The simulation results also demonstrate that theimplementation on an SIMD architecture can furtheraccelerate the proposed scheme by more than 93%.69ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 70. 70References1. “FPGA Implementation of a Novel, Fast Motion Estimation Algorithm for Real-Time VideoCompression”, FPGA 2001, CA. USA, S. Ramachandran and S. Srinivasan, Feb. 20012. “Image & Video Compression for Multimedia Engineering”, Y.Q. Shi and H. Sun, 20003. “A New Diamond Search Algorithm for Fast Block-Matching Motion Estimation”, IEEE Trans. ImageProcessing, S. Zhu and K. K. Ma, Feb. 20004. “A Novel Four-Step Search Algorithm for Fast Block Motion Estimation”, IEEE Trans. Circuits System,Video Technology, L. M. Po and W. C. Ma, June 19965. “Successive Elimination Algorithm for Motion Estimation” W. Li and E. Salari IEEE Trans. , Jan. 19956. “A New Three-Step Search Algorithm for Block Motion Estimation”, IEEE Trans. Circuits System,Video Technology, R. Li, B. Zeng, and M.L. Liou, Aug. 19947. “Predictive Coding Based on Efficient Motion Estimation”, IEEE Trans. on communications, R.Srinivasan, K.R. Rao, Aug. 19858. “Motion Compensated Inter-Frame Coding for Video-Conferencing”, T. Koga, K. Iinuma, A. Hirano,Y. Iijima, and T. Ishiguro, Proc. NTC81, Nov. 19819. “Displacement Measurement and its Applications”, IEEE Trans. on communications, J.R. Jain andA.K Jain, Dec. 1981ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide
  • 71. 71ARAB ACADEMY-CAIRO Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures spring 2013 slide

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