Near InfraRed imagery colorization
Abstract:
This paper proposes a stacked conditional Generative Adversarial Network-based method for Near InfraRed (NIR) imagery colorization. We propose a variant architecture of Generative Adversarial Network (GAN) that uses multiple loss functions over a conditional probabilistic generative model. We show that this new architecture/loss-function yields better generalization and representation of the generated colored IR images. The proposed approach is evaluated on a large test dataset and compared to recent state of the art methods using standard metrics. 11 Approved for public release; unlimited distribution.
Año de publicación:
2018
Keywords:
Fuente:

Tipo de documento:
Other
Estado:
Acceso abierto
Áreas de conocimiento:
- Visión por computadora
- Ciencias de la computación
Áreas temáticas:
- Métodos informáticos especiales
- Filosofía de las bellas artes y artes decorativas
- Campos específicos y tipos de fotografía