Resource-constrained complexity-scalable video decoding via adaptive B-residual computation
Sharon S. Peng, Zhun Zhong · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
As media processing gradually migrates from hardware to software programmable platforms, the number of media processing functions added on the media processor grow even faster than the ever-increasing media processor power can support. Computational complexity scalable algorithms become powerful vehicles for implementing many time-critical yet complexity-constrained applications, such as MPEG2 video decoding. In this paper, we present an adaptive resource-constrained complexity scalable MPEG2 video decoding scheme that makes a good trade-off between decoding complexity and output quality. Based on the available computational resources and the energy level of B-frame residuals, the scalable decoding algorithm selectively decodes B-residual blocks to significantly reduce system complexity. Furthermore, we describe an iterative procedure designed to dynamically adjust the complexity levels in order to achieve the best possible output quality under a given resource constraint. Experimental results show that up to 20% of total computational complexity reduction can be obtained with satisfactory output visual quality.