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Compressed-Domain Techniques for Error-Resilient Video Transcoding Using RPS

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3 Author(s)
Yui-Lam Chan ; Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon ; Hoi-Kin Cheung ; Wan-Chi Siu

In video applications where video sequences are compressed and stored in a storage device for future delivery, the encoding process is typically carried out without enough prior knowledge about the channel characteristics of a network. Error-resilient transcoding plays an important role to provide an addition of resilience to the video data, where or whenever it is needed. Recently, a reference picture selection (RPS) scheme has been adopted in an error-resilient transcoder in order to reduce error effects for the already encoded video bitstream. In this approach, the transcoder learns through a feedback channel about the damaged parts of a previously coded frame and then decides to code the next P-frame not relative to the most recent, but to an older, reference picture, which is known to be error-free in the decoder. One straightforward approach of adopting RPS in error-resilient transcoding is to decode all the P-frames from the previously nearest I-frame to the current transmitted frame which is then re-encoded with a new reference frame; this can create undesirable complexity in the transcoder as well as introduce re-encoding errors. In this paper, some novel techniques are suggested for an effective implementation of RPS in the error-resilient transcoder with the minimum requirement on its complexity. All the proposed techniques will manipulate video data in the compressed domain such that the computational loading of the transcoder is greatly reduced. By utilizing these new compressed-domain techniques, we develop a new structure to handle various types of macroblocks in the transcoder which re-uses motion vectors and prediction errors from the encoded bitstream. Experimental results demonstrate that significant improvements in terms of transcoder complexity and quality of reconstructed video can be achieved by employing our compressed-domain techniques.

Published in:

IEEE Transactions on Image Processing  (Volume:18 ,  Issue: 2 )