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.¹¹Approved for public release; unlimited distribution.

Año de publicación:

2018

Keywords:

• Infrared Imagery colorization
• Generative Adversarial Network (GAN)
• Convolutional Neural Networks (CNN)

Fuente:

scopus

google