  In video streaming applications, a fixed set of bitrate-resolution pairs
(known as a bitrate ladder) is typically used during the entire streaming
session. However, an optimized bitrate ladder per scene may result in (i)
decreased storage or delivery costs or/and (ii) increased Quality of
Experience. This paper introduces a Just Noticeable Difference (JND)-aware
per-scene bitrate ladder prediction scheme (JASLA) for adaptive video-on-demand
streaming applications. JASLA predicts jointly optimized resolutions and
corresponding constant rate factors (CRFs) using spatial and temporal
complexity features for a given set of target bitrates for every scene, which
yields an efficient constrained Variable Bitrate encoding. Moreover,
bitrate-resolution pairs that yield distortion lower than one JND are
eliminated. Experimental results show that, on average, JASLA yields bitrate
savings of 34.42% and 42.67% to maintain the same PSNR and VMAF, respectively,
compared to the reference HTTP Live Streaming (HLS) bitrate ladder Constant
Bitrate encoding using x265 HEVC encoder, where the maximum resolution of
streaming is Full HD (1080p). Moreover, a 54.34% average cumulative decrease in
storage space is observed.
