IEEE Trans Image Process - Motion-compensated frame interpolation based on multihypothesis motion estimation and texture optimization.

Tópicos

{ motion(1329) object(1292) video(1091) }
{ imag(2830) propos(1344) filter(1198) }
{ problem(2511) optim(1539) algorithm(950) }
{ perform(999) metric(946) measur(919) }
{ imag(1947) propos(1133) code(1026) }
{ studi(1119) effect(1106) posit(819) }
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{ control(1307) perform(991) simul(935) }
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Resumo

A novel motion-compensated frame interpolation (MCFI) algorithm to increase video temporal resolutions based on multihypothesis motion estimation and texture optimization is proposed in this paper. Initially, we form multiple motion hypotheses for each pixel by employing different motion estimation parameters, i.e., different block sizes and directions. Then, we determine the best motion hypothesis for each pixel by solving a labeling problem and optimizing the parameters. In the labeling problem, the cost function is composed of color, shape, and smoothness terms. Finally, we refine the motion hypothesis field based on the texture optimization technique and blend multiple source pixels to interpolate each pixel in the intermediate frame. Simulation results demonstrate that the proposed algorithm provides significantly better MCFI performance than conventional algorithms.

Resumo Limpo

novel motioncompens frame interpol mcfi algorithm increas video tempor resolut base multihypothesi motion estim textur optim propos paper initi form multipl motion hypothes pixel employ differ motion estim paramet ie differ block size direct determin best motion hypothesi pixel solv label problem optim paramet label problem cost function compos color shape smooth term final refin motion hypothesi field base textur optim techniqu blend multipl sourc pixel interpol pixel intermedi frame simul result demonstr propos algorithm provid signific better mcfi perform convent algorithm

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