Get Algorithms, Complexity Analysis and VLSI Architectures for PDF

By Peter M. Kuhn

ISBN-10: 1441950885

ISBN-13: 9781441950888

ISBN-10: 1475744749

ISBN-13: 9781475744743

MPEG-4 is the multimedia typical for combining interactivity, ordinary and artificial electronic video, audio and computer-graphics. general purposes are: net, video conferencing, cellular videophones, multimedia cooperative paintings, teleteaching and video games. With MPEG-4 your next step from block-based video (ISO/IEC MPEG-1, MPEG-2, CCITT H.261, ITU-T H.263) to arbitrarily-shaped visible items is taken. this important step calls for a brand new technique for approach research and layout to fulfill the significantly larger flexibility of MPEG-4.
movement estimation is a significant a part of MPEG-1/2/4 and H.261/H.263 video compression criteria and has attracted a lot realization in learn and undefined, for the next purposes: it really is computationally the main challenging set of rules of a video encoder (about 60-80% of the full computation time), it has a excessive effect at the visible caliber of a video encoder, and it isn't standardized, hence being open to pageant.
Algorithms, Complexity research, and VLSI Architectures for MPEG-4Motion Estimation covers intimately each step within the layout of a MPEG-1/2/4 or H.261/H.263 compliant video encoder:

  • Fast movement estimation algorithms
  • Complexity research instruments
  • Detailed complexity research of a software program implementation of MPEG-4 video
  • Complexity and visible caliber research of quick movement estimation algorithms inside MPEG-4
  • Design house on movement estimation VLSI architectures
  • Detailed VLSI layout examples of (1) a excessive throughput and (2) a low-power MPEG-4 movement estimator.

Algorithms, Complexity research and VLSI Architectures for MPEG-4Motion Estimation is a crucial creation to varied algorithmic, architectural and process layout points of the multimedia ordinary MPEG-4. As such, all researchers, scholars and practitioners operating in photo processing, video coding or method and VLSI layout will locate this ebook of interest.

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Extra info for Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation

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A rate/distortion criterion, based on Lagrange optimization is given in [Lee 97a]. A two-step gradient-based diamond search algorithm was proposed by [Zhu 97] and [Zhu 98]. This algorithm is based on the observation, that 53% (in large motion case) - 99% (in small motion case) of the motion vectors are enclosed in a circular area with a radius of 2 pels around the zero motion vector. This algorithm uses two diamond search patterns, depicted in Fig. 16. The large diamond search pattern (LDSP) is used for the gradient-based coarse search.

As usually a predetermined A is used, the multiplication of eq. 18) has to be performed only once per frame / VOP, when the lookup-table is updated. With every search step of the motion estimation algorithm only one additional addition operation is required therefore. 4 FAST MOTION ESTIMATION ALGORITHMS: AN OVERVIEW For battery powered real-time visual communications applications, there are stringent requirements on low power consumption. 22 GByte/s (as calculated before, eq. 5)) for the full-search motion estimation algorithm to encode a elF sized video at 30 fps, is not feasible at low power constraints using today's processor technology.

MV prediction is taken as the median of the previous, the above, and the above right MVs. The remaining motion vectors are searched using a spiral search scheme around the zero motion vector at positions which satisfy the RID extended inequality relation. BBM (Binary Block-matching) BBM (Binary Block-Matching) was proposed together with a VLSI architecture in [Nat 96], [Nat 97] and similar in [Miz 96]. 52) in which 0 denotes the exclusive-or operation and Fdi,j) is a low-complexity preprocessing filter for binary edge extraction of the search window and the reference block.

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Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation by Peter M. Kuhn


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