Hybrid Video Coding Based on Bidimensional Matching Pursuit

Abstract

<p/> <p>Hybrid video coding combines together two stages: first, motion estimation and compensation predict each frame from the neighboring frames, then the prediction error is coded, reducing the correlation in the spatial domain. In this work, we focus on the latter stage, presenting a scheme that profits from some of the features introduced by the standard H.264/AVC for motion estimation and replaces the transform in the spatial domain. The prediction error is so coded using the matching pursuit algorithm which decomposes the signal over an appositely designed bidimensional, anisotropic, redundant dictionary. Comparisons are made among the proposed technique, H.264, and a DCT-based coding scheme. Moreover, we introduce fast techniques for atom selection, which exploit the spatial localization of the atoms. An adaptive coding scheme aimed at optimizing the resource allocation is also presented, together with a rate-distortion study for the matching pursuit algorithm. Results show that the proposed scheme outperforms the standard DCT, especially at very low bit rates.</p

Image compression using an edge adapted redundant dictionary and wavelets

“…In this paper we use a technique based on the greedy Matching Pursuit algorithm that in general is not sparsenesspreserving [8]. However experimental results showed its ability to give highly sparse decompositions of 1-D signals [9], images [10,11] and videos [12,13]. Moreover very recent theoretical results prove that, under certain conditions, MP iteratively selects the atoms that give the sparsest representation.…”