Adaptively weighted update steps in motion compensated lifting based scalable video compression

Motion-compensated temporal wavelet decomposition is a useful framework for fully scalable video compression schemes. In this paper we propose a new approach to reduce the ghosting artifacts in low-pass temporal subbands; we adaptively weight the update steps according to the energy in the high-pass temporal subbands at the corresponding location. Experimental results show that the proposed algorithm can substantially remove ghosting from low-pass temporal frames. Importantly, at full frame-rate, the proposed algorithm has similar performance to the original motion-compensated temporal decomposition, with superior performance where the motion model fails signicantly. While entirely skipping the update steps accomplishes a similar objective, we show that the proposed method for adaptively weighting the update steps has better performance, especially in the presence of additive noise. Since the compressed bit-stream is scalable, the decoder does not generally have exactly the same infor...

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Nagita Mehrseresht, David Taubman
• Keywords: ICIP 2003, Image Processing, Low-pass Temporal Frames, Low-pass Temporal Subbands, Motion-compensated Temporal Decomposition, Temporal Wavelet Decomposition, Update Steps