%0 Journal Article %T Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Images %A Xavier Soria %A Angel Sappa %A Riad I. Hammoud %J Sensors %D 2018 %V 18 %N 7 %F Xavier Soria2018 %O ADAS; MSIAU; 600.086; 600.130; 600.122; 600.118 %O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3145), last updated on Tue, 25 Jan 2022 09:56:41 +0100 %X Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700–1100 nm) cross-talking with the visible bands (400–700 nm).This paper proposes two deep learning-based architectures to recover the full RGB color images, thus removing the NIR information from the visible bands. The proposed approaches directly restore the high-resolution RGB image by means of convolutional neural networks. They are evaluated with several outdoor images; both architectures reach a similar performance when evaluated in differentscenarios and using different similarity metrics. Both of them improve the state of the art approaches. %K RGB-NIR sensor %K multispectral imaging %K deep learning %K CNNs %U https://doi.org/10.3390/s18072059 %U http://refbase.cvc.uab.es/files/SSH2018.pdf %U http://dx.doi.org/10.3390/s18072059 %P 2059