A Subjective Study on Videos at Various Bit Depths

Bit depth adaptation, where the bit depth of a video sequence is reduced before transmission and up-sampled during display, can potentially reduce data rates with limited impact on perceptual quality. In this context, we conducted a subjective study on a UHD video database, BVI-BD, to explore the relationship between bit depth and visual quality. In this paper, three bit depth adaptation methods are investigated, including linear scaling, error diffusion, and a novel adaptive Gaussian filtering approach for up-sampling. The results from a subjective experiment indicate that above a critical bit depth, bit depth adaptation has no significant impact on perceptual quality, while reducing the amount information that is required to be transmitted. Below the critical bit depth, the more 'advanced' adaptation methods can be used to retain 'good' visual quality down to around 2 bits per color channel for the experimental setup - far lower than the common 8 bits per color channel. A selection of image quality metrics were benchmarked on the subjective data, and analysis indicates that a bespoke quality metric may be required to enable accurate bit depth adaptation.