This paper introduces a novel image error concealment technique, wherein the correlation among the correctly received pixels is implicitly exploited to recover the missing areas. This correlation is modeled as sparse representations of the correctly received surrounding areas of a lost regions, hence as a linear combination of very few atoms chosen from an over-complete dictionary. Under mild conditions, the sparse representation coefficients of a given zone, including both known and unknown pixels, can be correctly recovered from the sparse representation coefficients of its neighboring area. This linear process coupled with a simple smoothing process introduces a high quality concealed image. Compared with the state-of-the-art error concealment algorithms, experimental results show that the proposed method has better reconstruction performance in terms of objective and subjective evaluations.