Analysis/synthesis coding of dynamic textures based on motion distribution statistics
Olena Chubach, Patrick Garus, Mathias Wien, Jens-Rainer Ohm · 2017
This paper presents improvements to a dynamic texture synthesis approach which is based on motion distribution statistics, able to produce high visual quality of synthesised dynamic textures. The aim is to recreate synthetically highly textured regions like water, leaves and smoke, instead of processing them with a conventional codec such as HEVC. The method involves two steps: analysis, where motion distribution statistics are computed, and synthesis, where the texture region is synthesized. Dense optical flow is utilized for estimating the random motion of dynamic textures. The performance of our dynamic texture analysis and synthesis approach is tested on cropped sequences, containing water, leaves and smoke. Simulation results show potential bitrate savings up to 50% on texture sequences at comparable visual quality.