Filling-in Gaps in Textured Images Using Bit-Plane Statistics

In this paper we propose a novel approach for the texture analysis-synthesis problem, with the purpose torestore missing zones in greyscale images. Bit-plane decomposition is used, and a dictionary is build withbit-blocks statistics for each plane. Gaps are reconstructed with a conditional stochastic process, topropagate texture global features into the damaged area, using information stored in the dictionary. Ourrestoration method is simple, easy and fast, with very good results for a large set of textured images. Resultsare compared with a state-of-the-art restoration algorithm.