A Fast Wavelet Entropy Decoder for Scalable Video

In the RESUME project (Reconfigurable Embedded Systems for Use in Multimedia Environments) we explore the benefits of an implementation of scalable multimedia applications using reconfigurable hardware by building an FPGA implementation of a scalable wavelet-based video decoder. The term ‘scalable’ refers to a design that can easily accommodate changes in quality of service with minimal computational overhead. This is important for portable devices that have different Quality of Service (QoS) requirements and have varying power restrictions. The scalable video decoder consists of three major blocks: a Wavelet Entropy Decoder (WED), an Inverse Discrete Wavelet Transformer (IDWT) and a Motion Compensator (MC). The WED decodes entropy encoded parts of the video stream into wavelet transformed frames. These frames are decoded bitlayer per bitlayer. The more bitlayers are decoded the higher the image quality (scalability in image quality). Resolution scalability is obtained as an inherent property of the IDWT and frame rate scalability is acquired through hierarchical motion compensation. In this paper we present the results of our investigation into the hardware implementation of such a scalable video codec. In particular we found that the implementation of the entropy codec is a significant bottleneck. We present an alternative, hardware-friendly algorithm for entropy coding with superior data locality (both temporal and spatial), streaming capabilities, a high degree of parallelism, a small memory footprint and superior compression while maintaining all required scalability properties. We support these claims with synthesis results of an effective hardware implementation on an FPGA. The design was elaborated in VHDL and co-simulated with an extensive SystemC testbench. We obtained a real compact implementation which can easily decode the required 50 million symbols per second.