BLADE: Filter Learning for General Purpose Computational Photography

2018 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL PHOTOGRAPHY (ICCP)(2017)

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摘要
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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关键词
general purpose computational photography,computationally efficient image upscaling method,BLADE,trainable edge-adaptive filtering framework,rapid and accurate image super resolution method,best linear adaptive enhancement,adaptive filtering framework
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