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Fast Image Interpolation via Random Forests
2015
IEEE Transactions on Image Processing
This paper proposes a two-stage framework for fast image interpolation via random forests (FIRF). The proposed FIRF method gives high accuracy, as well as requires low computation. The underlying idea of this proposed work is to apply random forests to classify the natural image patch space into numerous subspaces and learn a linear regression model for each subspace to map the low-resolution image patch to high-resolution image patch. The FIRF framework consists of two stages. Stage 1 of the
doi:10.1109/tip.2015.2440751
pmid:26054066
fatcat:wy4xbqfewrdrplpwm7zjxyhgbu