Clustering-based methods for fast epitome generation

This paper deals with epitome generation, mainly dedicated here to image coding applications. Existing approaches are known to be memory and time consuming due to exhaustive self-similarities search within the image for each non-overlapping block. We propose here a novel approach for epitome construction that first groups close patches together. In a second time the self-similarities search is performed for each group. By limiting the number of exhaustive searches we limit the memory occupation and the processing time. Results show that interesting complexity reduction can be achieved while keeping a good epitome quality (down to 18.08 % of the original memory occupation and 41.39%of the original processing time).