BLADE: Filter Learning for General Purpose Computational Photography
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Pascal Getreuer, Ignacio Garcia-Dorado, John Isidoro, Sungjoon Choi,
Frank Ong, Peyman Milanfar
2017
Abstract
The Rapid and Accurate Image Super Resolution (RAISR) method of Romano,
Isidoro, and Milanfar is a computationally efficient image upscaling method
using a trained set of filters. We describe a generalization of RAISR, which we
name Best Linear Adaptive Enhancement (BLADE). This approach is a trainable
edge-adaptive filtering framework that is general, simple, computationally
efficient, and useful for a wide range of problems in computational
photography. We show applications to operations which may appear in a camera
pipeline including denoising, demosaicing, and stylization.
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