Aurélie Martin

Atomic decomposition dedicated to AVC and spatial SVC prediction

This work, we propose the use of sparse signal representation techniques to solve the problem of closed-loop spatial image prediction. The reconstruction of signal in the block to predict is based on basis functions selected with the matching pursuit (MP) iterative algorithm, to best match a causal neighborhood. We evaluate this new method in terms of PSNR and bitrate in a H.264/AVC encoder. Experimental results indicate an improvement of rate-distortion performance. In this paper, we also present results concerning the use of this technique for intra-inter layer prediction refinement, in a scalable video coding (SVC) like scheme.

Phase refinement for image prediction based on sparse representation

In this work, we propose the use of sparse signal representation techniques to solve the problem of closed-loop spatial image prediction. The reconstruction of signal in the block to predict is based on basis functions selected with the Matching Pursuit (MP) iterative algorithm, to best match a causal neighborhood. We evaluate this new method in terms of PSNR and bitrate in a H.264 / AVC encoder. Experimental results indicate an improvement of rate-distortion performance. In this paper, we also present results concerning the use of phase correlation to improve the reconstruction trough shifted-basis functions.

Sparse representations for spatial prediction and texture refinement

In this work, we propose a novel approach for signal prediction based on the use of sparse signal representations and Matching Pursuit (MP) techniques. The paper first focuses on spatial texture prediction in a conventional block-based hybrid coding scheme and secondly addresses inter-layer prediction in a scalable video coding (SVC) framework. For spatial prediction the signal reconstruction of the block to predict is based on basis functions selected with the MP iterative algorithm, to best match a causal neighborhood. Inter-layer MP based prediction employs base layer upsampled components additionally to the causal neighborhood in order to improve the representation of high frequencies. New solutions are proposed for efficiently deriving and exploiting the atoms dictionary through phase refinement and mono-dimensional basis functions. Experimental results indicate noticeable improvement of rate/distortion performance compared to the standard prediction methods as specified in H.264/AVC and its extension SVC.