Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Images

• Main Authors: Xavier Soria, Angel D. Sappa, Riad I. Hammoud
• Format: Article
• Language: English
• Published: MDPI AG 2018-06-01
• Series: Sensors
• Subjects: RGB-NIR sensor; multispectral imaging; deep learning; CNNs
• Online Access: http://www.mdpi.com/1424-8220/18/7/2059

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 different scenarios and using different similarity metrics. Both of them improve the state of the art approaches.