Performance and Complexity Co-evaluation of the Advanced Video Coding Standard for Cost-Effective Multimedia Communications

Abstract

The advanced video codec (AVC) standard, recently defined by a joint video team (JVT) of ITU-T and ISO/IEC, is introduced in this paper together with its performance and complexity co-evaluation. While the basic framework is similar to the motion-compensated hybrid scheme of previous video coding standards, additional tools improve the compression efficiency at the expense of an increased implementation cost. As a first step to bridge the gap between the algorithmic design of a complex multimedia system and its cost-effective realization, a high-level co-evaluation approach is proposed and applied to a real-life AVC design. An exhaustive analysis of the codec compression efficiency versus complexity (memory and computational costs) project space is carried out at the early algorithmic design phase. If all new coding features are used, the improved AVC compression efficiency (up to 50% compared to current video coding technology) comes with a complexity increase of a factor 2 for the decoder and larger than one order of magnitude for the encoder. This represents a challenge for resource-constrained multimedia systems such as wireless devices or high-volume consumer electronics. The analysis also highlights important properties of the AVC framework allowing for complexity reduction at the high system level: when combining the new coding features, the implementation complexity accumulates, while the global compression efficiency saturates. Thus, a proper use of the AVC tools maintains the same performance as the most complex configuration while considerably reducing complexity. The reported results provide inputs to assist the profile definition in the standard, highlight the AVC bottlenecks, and select optimal trade-offs between algorithmic performance and complexity

Complexity/Performance Analysis of a H.264/AVC Video Encoder

“…Comparisons with MPEG 4 Part2, simple profile with a 16 search size, half pixel resolution and I and P pictures are provided in (Saponara et al, 2004). For the memory usage, MPEG4 requires 2.97 MB for the QCIF and 9.88 for the CIF sequences.…”

“…For a H.264 encoder using all the new coding features, more than 50% average bit saving with 1-2 dB PSNR (Peak Signal-to-Noise Ratio) video quality gain are achieved compared to previous video encoding standards (Saponara et al, 2004). However, this comes with a complexity increase of a factor 2 for the decoder and larger than one order of magnitude for the encoder (Saponara et al, 2004). Implementing a H.264/AVC video encoder represents a big challenge for resourceconstrained multimedia systems such as wireless devices or high-volume consumer electronics since this requires very high computational power to achieve real-time encoding.…”

“…Such a standard uses advanced compression techniques that in turn, require high computational power (Alvarez et al, 2005). For a H.264 encoder using all the new coding features, more than 50% average bit saving with 1-2 dB PSNR (Peak Signal-to-Noise Ratio) video quality gain are achieved compared to previous video encoding standards (Saponara et al, 2004). However, this comes with a complexity increase of a factor 2 for the decoder and larger than one order of magnitude for the encoder (Saponara et al, 2004).…”

“…Processing time metrics are completed by memory cost measures as this have a dominant impact on the cost-effective realization of multimedia systems for both hardware and software based platforms (Catthoor et al, 2002), (Chimienti et al, 2002). Actually, when combining the new coding features, the implementation complexity accumulates, while the global compression efficiency becomes saturated (Saponara et al, 2004). To find an optimal balance between the coding efficiency and the implementation cost, a proper use of the AVC tools is needed to maintain the same coding performance as the most complex coding parameters configuration (all tools on) while considerably reducing complexity.…”

A toolset for the analysis and optimization of motion estimation algorithms and processors

“…New advanced coding standards, such as VC-1, AVS and H.264 [1], make use of advanced techniques to achieve high compression. Previous work [2] shows that motion estimation is the most expensive operation in the H.264 encoder, representing up to 90% of the total complexity. This makes it desirable to have specialized hardware for motion estimation.…”