PT Unknown
AU Xavier Soria
   Angel Sappa
   Arash Akbarinia
TI Multispectral Single-Sensor RGB-NIR Imaging: New Challenges and Opportunities
BT 7th International Conference on Image Processing Theory, Tools & Applications
PY 2017
DE Color restoration; Neural networks; Singlesensor cameras; Multispectral images; RGB-NIR dataset
AB Multispectral images captured with a single sensor camera have become an attractive alternative for numerous computer vision applications. However, in order to fully exploit their potentials, the color restoration problem (RGB representation) should be addressed. This problem is more evident in outdoor scenarios containing vegetation, living beings, or specular materials. The problem of color distortion emerges from the sensitivity of sensors due to the overlap of visible and near infrared spectral bands. This paper empirically evaluates the variability of the near infrared (NIR) information with respect to the changes of light throughout the day. A tiny neural network is proposed to restore the RGB color representation from the given RGBN (Red, Green, Blue, NIR) images. In order to evaluate the proposed algorithm, different experiments on a RGBN outdoor dataset are conducted, which include various challenging cases. The obtained result shows the challenge and the importance of addressing color restoration in single sensor multispectral images.
ER