Share Email Print
cover

Journal of Electronic Imaging • new

Artistic photo filter removal using convolutional neural networks
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We present a method for the automatic restoration of images subjected to the application of photographic filters, such as those made popular by photo-sharing services. The method uses a convolutional neural network (CNN) for the prediction of the coefficients of local polynomial transformations that are applied to the input image. The experiments we conducted on a subset of the Places-205 dataset show that the quality of the restoration performed by our method is clearly superior to that of traditional color balancing and restoration procedures, and to that of recent CNN architectures for image-to-image translation.

Paper Details

Date Published: 23 December 2017
PDF: 14 pages
J. Electron. Imag. 27(1) 011004 doi: 10.1117/1.JEI.27.1.011004
Published in: Journal of Electronic Imaging Volume 27, Issue 1
Show Author Affiliations
Simone Bianco, Univ. degli Studi di Milano-Bicocca (Italy)
Claudio Cusano, Univ. degli Studi di Pavia (Italy)
Flavio Piccoli, Univ. degli Studi di Milano-Bicocca (Italy)
Raimondo Schettini, Univ. degli Studi di Milano-Bicocca (Italy)


© SPIE. Terms of Use
Back to Top