BLADE: Filter Learning for General Purpose Computational Photography
Computer Vision and Pattern Recognition
2017-12-11 v2
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.
Cite
@article{arxiv.1711.10700,
title = {BLADE: Filter Learning for General Purpose Computational Photography},
author = {Pascal Getreuer and Ignacio Garcia-Dorado and John Isidoro and Sungjoon Choi and Frank Ong and Peyman Milanfar},
journal= {arXiv preprint arXiv:1711.10700},
year = {2017}
}