In this tutorial paper, we discuss the ITU-T H.263+ (or H.263 Version 2) low-bit-rate video coding standard. We first describe, briefly, the H.263 standard including its optional modes. We then address the 12 new negotiable modes of H.263+. Next, we present experimental results for these modes, based on our public-domain implementation (see our Web site at http://spmg.ece.ubc.ca). Tradeoffs among compression performance, complexity, and memory requirements for the H.263+ optional modes are discussed. Finally, results for mode combinations are presented.Index Terms-H.263, H.263+, video compression standards, video compression and coding, video conferencing, video telephony.
We present an efficient computation constrained block-based motion vector estimation algorithm for low bit rate video coding that yields good tradeoffs between motion estimation distortion and number of computations. A reliable predictor determines the search origin, localizing the search process. An efficient search pattern exploits structural constraints within the motion field. A flexible cost measure used to terminate the search allows simultaneous control of the motion estimation distortion and the computational cost. Experimental results demonstrate the viability of the proposed algorithm in low bit rate video coding applications. The resulting low bit rate video encoder yields essentially the same levels of rate-distortion performance and subjective quality achieved by the UBC H.263+ video coding reference software. However, the proposed motion estimation algorithm provides substantially higher encoding speed as well as graceful computational degradation capabilities.
We introduce a systematic approach to configuring the video encoding parameters for optimal video encoding in this paper. The determination of optimal video encoding parameters is formulated as an optimization problem of maximizing the expected video encoding quality under a set of constraints that may include a video quality measure, a target bitrate, computation, memory bandwidth, etc. We use the Video Quality Metric, a measurement paradigm of video quality that is based on algorithms for objective measurement of video quality, to measure the expected video encoding performance. The optimization problem can be solved through an efficient multidimensional numerical search method, direct simplex search method, with encoding of various sequences with different encoding parameter settings. We illustrate the approach to determine parameters to enable optimal MB level quantization parameter adaptation in H.264 / AVC.
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