Edge-aware spatial-frequency extrapolation for consecutive block loss.

Abstract

To improve the spatial error concealment (SEC) for consecutive block loss, an edge-aware spatial-frequency extrapolation (ESFE) algorithm and its edge-guided parametric model are proposed by selectively incorporating the Hough-based edge synthesis into the frequency-based extrapolation architecture. The dominant edges that cross the missing blocks are firstly identified by the Canny detector, and then the robust Hough transformation is utilized to systematically connect these discontinuous edges. During the generation of edge-guided parametric model, the synthesized edges are utilized to divide the missing blocks into the structure-preserving regions, and thus the residual error is reliably reduced. By successively minimizing the weighted residual error and updating the parametric model, the known samples are approximated by a set of basis functions which are distributed in a region containing both known and unknown samples. Compared with other state-of-the-art SEC algorithms, experimental results show that the proposed ESFE algorithm can achieve better reconstruction quality for consecutive block loss while keeping relatively moderate computational complexity.