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

Just Noticeable Difference-aware Per-Scene Bitrate-laddering for Adaptive Video Streaming