EFFICIENT AGGREGATION VIA ITERATIVE BLOCK-BASED ADAPTING SUPPORT-WEIGHTS

Local stereo matching algorithms based on adapting-weights aggregation produce excellent results compared to other lo- cal methods. In particular, they produce more accurate results near disparity edges. This improvement is obtained thanks to the fact that the support for each pixel is accurately deter- mined based on information such as colour or spatial distance. However, the computation of the support for each pixel results in computationally complex algorithms, especially when us- ing large aggregation windows. Iterative aggregation schemes are a potential alternative to using large windows. In this paper we propose a novel iterative approach for adapting- weights aggregation which produces better results and out- performs most previous adapting-weights methods.