4.6 Article

Super Resolution Infrared Thermal Imaging Using Pansharpening Algorithms: Quantitative Assessment and Application to UAV Thermal Imaging

Journal

SENSORS
Volume 21, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/s21041265

Keywords

thermal imaging; infrared; pansharpening; resolution enhancement; multispectral; super-resolution; remote sensing

Funding

  1. Spanish Ministerio de Ciencia, Innovacion y Universidades [RTI2018-093874-B-100]
  2. MINECO research project AQUARISK [CGL2017-86241-R]
  3. CAM research project LABPA-CM [H2019/HUM-5692]
  4. Premio Arce Foundation

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This study focuses on analyzing the potential of applying pansharpening algorithms to thermal images, comparing them with thermal images obtained from UAVs, in order to select the best method for quantitative results. The objective selection of methods for this type of images has not been done before, and it has important applications in fields such as heritage documentation.
The lack of high-resolution thermal images is a limiting factor in the fusion with other sensors with a higher resolution. Different families of algorithms have been designed in the field of remote sensors to fuse panchromatic images with multispectral images from satellite platforms, in a process known as pansharpening. Attempts have been made to transfer these pansharpening algorithms to thermal images in the case of satellite sensors. Our work analyses the potential of these algorithms when applied to thermal images from unmanned aerial vehicles (UAVs). We present a comparison, by means of a quantitative procedure, of these pansharpening methods in satellite images when they are applied to fuse high-resolution images with thermal images obtained from UAVs, in order to be able to choose the method that offers the best quantitative results. This analysis, which allows the objective selection of which method to use with this type of images, has not been done until now. This algorithm selection is used here to fuse images from thermal sensors on UAVs with other images from different sensors for the documentation of heritage, but it has applications in many other fields.

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