Uncooled Infrared Image Deblurring

this is dataset for our paper: "Large-scale Benchmark for Uncooled Infrared Image Deblurring", submitted for IEEE SIgnal Processing Letters.

the abstract for paper is :
Infrared images are increasingly adopted in various applications. Therefore, motion deblurring for infrared images is also receiving growing interest. However, deep learning-based deblurring techniques for infrared images have yet to be deeply studied, since there is no publicly available dataset for training and evaluating the networks. In this letter, we introduce a large-scale dynamic motion deblurring dataset for microbolometer-based uncooled infrared detectors named Uncooled Infrared Image Deblurring (UIRD), which reflects their unique blur characteristics. The dataset is generated using a combination of a cooled infrared camera, frame interpolation, IR band conversion, and a unique blur accumulation model. Benchmark results on our dataset with state-of-the-art deep learning-based deblurring algorithms are reported, and we also show the effectiveness of our dataset by showing deblurring results on real uncooled infrared images. Our dataset is publicly released to facilitate future research in this area.