Rate-distortion optimization for stereoscopic video streaming with unequal error protection
EURASIP Journal on Applied Signal Processing - 3DTV: Capture, Transmission, and Display of 3D Video
Soft decision quantization for H.264 with main profile compatibility
IEEE Transactions on Circuits and Systems for Video Technology
Laplace distribution based Lagrangian rate distortion optimization for hybrid video coding
IEEE Transactions on Circuits and Systems for Video Technology
An improved R-D optimized motion estimation method for video coding
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
A computation approach to the minimum total rate problem of causal video coding
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Full rate distortion optimization of MPEG-2 video coding
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Classified region algorithm for fast intermode decision in H.264/AVC encoder
EURASIP Journal on Advances in Signal Processing
Joint optimization coding for level and map information in H.264/AVC
Image Communication
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Rate distortion (RD) optimization for H.264 interframe coding with complete baseline decoding compatibility is investigated on a frame basis. Using soft decision quantization (SDQ) rather than the standard hard decision quantization, we first establish a general framework in which motion estimation, quantization, and entropy coding (in H.264) for the current frame can be jointly designed to minimize a true RD cost given previously coded reference frames. We then propose three RD optimization algorithms-a graph-based algorithm for near optimal SDQ in H.264 baseline encoding given motion estimation and quantization step sizes, an algorithm for near optimal residual coding in H.264 baseline encoding given motion estimation, and an iterative overall algorithm to optimize H.264 baseline encoding for each individual frame given previously coded reference frames-with them embedded in the indicated order. The graph-based algorithm for near optimal SDQ is the core; given motion estimation and quantization step sizes, it is guaranteed to perform optimal SDQ if the weak adjacent block dependency utilized in the context adaptive variable length coding of H.264 is ignored for optimization. The proposed algorithms have been implemented based on the reference encoder JM82 of H.264 with complete compatibility to the baseline profile. Experiments show that for a set of typical video testing sequences, the graph-based algorithm for near optimal SDQ, the algorithm for near optimal residual coding, and the overall algorithm achieve on average, 6%, 8%, and 12%, respectively, rate reduction at the same PSNR (ranging from 30 to 38 dB) when compared with the RD optimization method implemented in the H.264 reference software.