Title :
When is bit allocation for predictive video coding easy?
Author :
Sermadevi, Yegnaswamy ; Chen, Jun ; Hemami, Sheila S. ; Berger, Toby
Author_Institution :
Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA
Abstract :
This paper addresses the problem of bit allocation among frames in a predictively encoded video sequence. Finding optimal solutions to this problem potentially requires making an exponential number of calls to the encoder. To better understand the structure of the rate-distortion data output by video encoders, a simple model of a sequentially encoded autoregressive Gaussian random field is theoretically investigated. The rate-distortion data for the model exhibits an additive-separability property, i.e. the rate can be decomposed into a sum of independent functions of single distortion variables. This property implies the near-optimal behavior of a non-backtracking steepest-descent (SD) based bit allocation algorithm. The SD algorithm when applied to video coding produces near-optimal solutions by making a linear number of calls to the encoder. Results are presented for MPEG-2 encoding of standard video sequences.
Keywords :
Gaussian distribution; autoregressive processes; code standards; optimisation; rate distortion theory; video coding; MPEG-2 encoding; additive-separability property; autoregressive Gaussian random field; bit allocation; near-optimal behavior; nonbacktracking steepest descent; optimal solutions; predictive video coding; predictively encoded video sequence; rate-distortion data; sequentially encoded random field; video encoders; Bit rate; Data compression; Encoding; MPEG 4 Standard; Prediction algorithms; Quantization; Rate distortion theory; Rate-distortion; Video coding; Video sequences;
Conference_Titel :
Data Compression Conference, 2005. Proceedings. DCC 2005
Print_ISBN :
0-7695-2309-9
DOI :
10.1109/DCC.2005.96