RGB-Guided Resolution Enhancement of IR Images

TL;DR

This paper presents GIRRE, a novel RGB-guided method for enhancing the resolution of low-res IR images using high-res color images, achieving significant PSNR improvements over existing techniques.

Contribution

GIRRE introduces a new multi-image super resolution approach that leverages RGB images to significantly improve IR image resolution beyond current methods.

Findings

Achieves an average PSNR gain of 1.2 dB.

Up to 1.8 dB PSNR improvement.

Visually noticeable enhancement in IR image quality.

Abstract

This paper introduces a novel method for RGB-Guided Resolution Enhancement of infrared (IR) images called Guided IR Resolution Enhancement (GIRRE). In the area of single image super resolution (SISR) there exists a wide variety of algorithms like interpolation methods or neural networks to improve the spatial resolution of images. In contrast to SISR, even more information can be gathered on the recorded scene when using multiple cameras. In our setup, we are dealing with multi image super resolution, especially with stereo super resolution. We consider a color camera and an IR camera. Current IR sensors have a very low resolution compared to color sensors so that recent color sensors take up 100 times more pixels than IR sensors. To this end, GIRRE increases the spatial resolution of the low-resolution IR image. After that, the upscaled image is filtered with the aid of the high-resolution color image. We show that our method achieves an average PSNR gain of 1.2 dB and at best up to 1.8 dB compared to state-of-the-art methods, which is visually noticeable.