FGS Coding Using Cycle-Based Leaky Prediction Through Multiple Leaky Factors

This paper proposes a fine granularity scalable (FGS) coding using cycle-based leaky prediction, in which the multiple leaky factors are used to yield enhancement layer prediction to make a good compromise between coding efficiency and drift error. In this proposed method, first, the error propagation for leaky prediction with two leaky factors is theoretically analyzed in case only the base-layer bitstream and part of the enhancement-layer bitstream are available at the decoder. Based on this analysis, in this paper, we investigate how to effectively introduce enhancement-layer information into the prediction loop for enhancement-layer coding by the proper leaky factors to constrain drift error while keeping high coding efficiency. Furthermore, a coefficient scaling approach in the transform domain is proposed to address the decoding complexity issue for multiple reconstructions of partial enhancement layers at different quality levels. Finally, an encoder optimization approach is presented to further control drift error for multiple FGS layers coding. The experimental results show that compared to AR-FGS in JSVM, the proposed method can significantly improve the coding performance over a wide range of bitrates.

I. Introduction

Aseries of nonscalable hybrid video coders such as MPEG-x and H.26x has been successfully developed. The latest video coding standard H.264/AVC [1] jointly developed by ISO and ITU provides more than 50% bitrate saving against MPEG-2 video coding standard [2] at the same quality and also contains many network-friendly features. However, the generated nonscalable bitstream cannot adapt to video transmission well on time-varying networks including wireless and cable channels or terminal devices with different processing capabilities regarding available memory, computation power and accessible bandwidth etc. Scalable video coding is more effective to address these situations since its generated bitstream is decodable at different bit-rates which may have different quality levels, temporal or spatial resolutions etc.