Image reconstruction from dense binary pixels

Or Litany; Tal Remez; Alex Bronstein

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arXiv · 1512.01774

Image reconstruction from dense binary pixels

Or Litany·Tal Remez·Alex Bronstein

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Abstract

Recently, the dense binary pixel Gigavision camera had been introduced, emulating a digital version of the photographic film. While seems to be a promising solution for HDR imaging, its output is not directly usable and requires an image reconstruction process. In this work, we formulate this problem as the minimization of a convex objective combining a maximum-likelihood term with a sparse synthesis prior. We present MLNet - a novel feed-forward neural network, producing acceptable output quality at a fixed complexity and is two orders of magnitude faster than iterative algorithms. We present state of the art results in the abstract.

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Or Litany, Tal Remez, Alex Bronstein. 2015-12-06. Image reconstruction from dense binary pixels. https://arxiv.org/abs/1512.01774

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