Infrared imagery super-resolution by using a generative adversarial network

Trong-An Bui, Pei‐Jun Lee, Kuan‐Min Lee, Walter Wang, Shiual-Hal Shiu · 2021

The thermal camera often has a limited spatial resolution compared to the RGB camera with typically provides megapixels of resolution. This study presents a super-resolution architecture for infrared (IR) imagery base on a generative adversarial network. The up-sampling in this proposed network’s design generates a new super-resolution image by four times. Moreover, in this paper, generative network and discriminative models for IR images are presented. The small-object features in super-resolution IR images are shown in the simulation section with high quality.

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