Scene-Adaptive Transform Domain Video Partitioning

Abstract

An adaptive mechanism for video partitioning in the transform domain is proposed. Different quantitative measures for motion complexity and activity levels in a scene are defined, based on which a video scene can be consistently categorised into identifiable classes. Further, the video quality, as measured by the mean square error (MSE) is related to certain parameters used in video partitioning. Adaptability is realized by tailoring the parameters of the video partitioning algorithm to the specific characteristics of the video scene, as embodied in the video scene class and the video quality. Experimental results are included.