By Peter M. Kuhn
MPEG-4 is the multimedia general for combining interactivity, common and artificial electronic video, audio and computer-graphics. regular functions 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 crucial step calls for a brand new technique for procedure research and layout to fulfill the significantly better flexibility of MPEG-4.
movement estimation is a imperative a part of MPEG-1/2/4 and H.261/H.263 video compression criteria and has attracted a lot awareness in learn and undefined, for the subsequent purposes: it really is computationally the main tough set of rules of a video encoder (about 60-80% of the entire computation time), it has a excessive impression at the visible caliber of a video encoder, and it's not standardized, therefore being open to festival.
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 speedy movement estimation algorithms inside MPEG-4
- Design area 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 vital creation to varied algorithmic, architectural and procedure layout points of the multimedia common MPEG-4. As such, all researchers, scholars and practitioners operating in photo processing, video coding or approach and VLSI layout will locate this booklet of interest.
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Extra info for Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation
To give an overview of the state-of-the-art of fast motion estimation algorithms, cf. the rest of this chapter. 2. To analyze the trade-off of complexity-reduced motion estimation versus image quality degradation with respect to the PSNRfbit rate for rectangular video objects, as well as for binary-shaped video objects supported by MPEG-4. 3. To evaluate the implementation complexity on typical processor architectures and for (parallelized) VLSI implementations, cf. chapter 5 and 8. 1 Classification of fast motion estimation algorithms Fig.
I I 1 - ' ... ' - ... -t ... - 1 "', '" i ~ r !.. ' - ' - '" I -:->; -;-:- -> -'. - f I ... ,- r -. - i' _ 1_ ........ 1- ... :_ ~ _: ... : _ T -, - ,. , I I 'I' " .. ' .. 1,. I I I i -, - i J • ; . . . . . . _ _ _ _• I I I - , . T - , - (" "\ - tOo T" -," r ..... ,- _,_ 1 J .. ,_ " '- tit _ I .. I ,_ I I , _I .. I I J I , 1 J .. 12: a) 2DLOG (2D logarithmic search), b) TSS (Three Step Search) I 34 CHAPTER 2 TSS: Three Step Search TSS (Three Step Search, also : 3SS) was proposed by [Koga 81] using a similar structure as 2DLOG, but with the use of MAD instead of the MSE.
BPM (Bit-Plane-Matching) In [Feng 95], [Feng 95a] BPM (Bit-Plane-Matching) was employed as the first step of a search range adaptive hierarchical scheme to determine candidate motion vectors, which are evaluated in a further step using the MAD criterion. 56) BFM (Block Feature Matching) The block feature-matching (BFM) criterion was introduced by [Luo 97], which allows an efficient VLSI implementation. 62) NxN Bits Binary Sign Vector: Nk(x,y) = [Nix,y)+Nk(x+l,y)+ ... 63) The weighting factor A.
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