PT Journal AU Xavier Soria Angel Sappa Riad I. Hammoud TI Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Images SO Sensors JI SENS PY 2018 BP 2059 VL 18 IS 7 DI 10.3390/s18072059 DE RGB-NIR sensor; multispectral imaging; deep learning; CNNs AB 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. ER