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A Single-Image Super-Resolution Algorithm for Infrared Thermal Images


Kiran Y, Shrinidhi V, W Jino Hans and N Venkateswaran


Vol. 17  No. 10  pp. 256-261


Infrared (IR) images are significant in several major fields such as security, military and landform determination. However, due to physical limitations of the precision optics and expensive image sensors, these images tend to have poor resolution. This paper presents a Single-image Super-Resolution (SISR) algorithm for IR thermal images which effectively reconstructs High-resolution (HR) image from its low-resolution (LR) counterpart without an external database. In this method, the training data set is built from in-place self-examples generated by a bi-pyramid of recursively scaled and subsequently interpolated image patches. The relation between self-example patch-pairs is learned by a regression operator represented as a matrix and used as a prior to super-resolve LR infrared thermal images. Subjective and objective evaluation of the proposed algorithm validates the efficiency of the proposed algorithm.


Remote sensing Super-resolution, Image-pair analysis, Regression operators