This paper examines the application of a deep learning approach to converting night-time images to day-time images. In particular, we show that a convolutional neural network enables the simulation of artificial and ambient light on images. In this paper, we illustrate the design of the deep neural network and some preliminary results on a real indoor environment and two virtual environments rendered with a 3D graphics engine. The experimental results are encouraging and confirm that a convolutional neural network is an interesting approach in the fields of photo-editing and digital image postprocessing.

Converting night-time images to day-time images through a deep learning approach

Capece, Nicola;Erra, Ugo;
2017-01-01

Abstract

This paper examines the application of a deep learning approach to converting night-time images to day-time images. In particular, we show that a convolutional neural network enables the simulation of artificial and ambient light on images. In this paper, we illustrate the design of the deep neural network and some preliminary results on a real indoor environment and two virtual environments rendered with a 3D graphics engine. The experimental results are encouraging and confirm that a convolutional neural network is an interesting approach in the fields of photo-editing and digital image postprocessing.
2017
9781538608319
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/132260
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