PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study

Mehrdad Shoeiby, Antonio Robles-Kelly, Ran Wei, Radu Timofte; The European Conference on Computer Vision (ECCV) Workshops, 2018, pp. 0-0

Abstract


This paper introduces a newly collected and novel dataset (StereoMSI) for example-based single and colour-guided spectral image super-resolution. The dataset was first released and promoted during the PIRM2018 spectral image super-resolution challenge. To the best of our knowledge, the dataset is the first of its kind, comprising 350 registered colour-spectral image pairs. The dataset has been used for the two tracks of the challenge and, for each of these, we have provided a split into training, validation and testing. This arrangement is a result of the challenge structure and phases, with the first track focusing on examplebased spectral image super-resolution and the second one aiming at exploiting the registered stereo colour imagery to improve the resolution of the spectral images. Each of the tracks and splits has been selected to be consistent across a number of image quality metrics. The dataset is quite general in nature and can be used for a wide variety of applications in addition to the development of spectral image super-resolution methods.

Related Material


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[bibtex]
@InProceedings{Shoeiby_2018_ECCV_Workshops,
author = {Shoeiby, Mehrdad and Robles-Kelly, Antonio and Wei, Ran and Timofte, Radu},
title = {PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study},
booktitle = {The European Conference on Computer Vision (ECCV) Workshops},
month = {September},
year = {2018}
}