Video-scaling algorithm based on human perception for spatio-temporal stimuli

Video conferencing and high quality video-on-demand services are very desirable for many Internet users. However, Internet access channels ranging from wireless connections to high-speed ATM networks mean great heterogeneity with respect to bandwidth. Hierarchical video encoders that scale and distribute video data over different layers enable users to adapt video quality to the capacity of their Internet connection. However, the construction of the layers at the encoder determines the video quality that can be expected at the receiver. To achieve an optimal configuration of the different layers with respect to visual quality, we propose a hybrid scaling algorithm that scales video data both in spatial and temporal dimension. Using a quality metric based on properties of the human visual system our algorithm calculates an optimal ratio between spatial and temporal information. Additionally, we present experimental results that demonstrate the capabilities of our approach.