Heterogeneous video transcoding to lower spatio-temporal resolutions and different encoding formats
T Shanableh, M Ghanbari - IEEE Transactions on Multimedia, 2000 - ieeexplore.ieee.org
IEEE Transactions on Multimedia, 2000•ieeexplore.ieee.org
In this work, transcoding of pre-encoded MPEG-1, 2 video into lower bit rates is realized
through altering the coding algorithm into H. 261/H. 263 standards with lower spatio-
temporal resolutions. For this heterogeneous transcoding, we extract and compose a set of
candidate motion vectors, from the incoming bit stream, to comply with the encoding format
of the output bit stream. For the spatial resolution reduction we generate one motion vector
out of a set of input motion vectors operating on the higher spatial resolution image. Finally …
through altering the coding algorithm into H. 261/H. 263 standards with lower spatio-
temporal resolutions. For this heterogeneous transcoding, we extract and compose a set of
candidate motion vectors, from the incoming bit stream, to comply with the encoding format
of the output bit stream. For the spatial resolution reduction we generate one motion vector
out of a set of input motion vectors operating on the higher spatial resolution image. Finally …
In this work, transcoding of pre-encoded MPEG-1, 2 video into lower bit rates is realized through altering the coding algorithm into H.261/H.263 standards with lower spatio-temporal resolutions. For this heterogeneous transcoding, we extract and compose a set of candidate motion vectors, from the incoming bit stream, to comply with the encoding format of the output bit stream. For the spatial resolution reduction we generate one motion vector out of a set of input motion vectors operating on the higher spatial resolution image. Finally, for the temporal resolution reduction we compose new motion vectors from the dropped frames motion vectors. Throughout the paper, we discuss the impact of motion estimation refinement on the new motion vectors and show that for all cases a simple half-pixel refinement is sufficient for near-optimum results.
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