PIRM2018 challenge on spectral image super-resolution: methods and results
conference contribution
posted on 2019-01-01, 00:00authored byMehrdad Shoeiby, Antonio Robles-KellyAntonio Robles-Kelly, Radu Timofte, Ruofan Zhou, Fayez Lahoud, Sabine Süsstrunk, Zhiwei Xiong, Zhan Shi, Chang Chen, Dong Liu, Zheng-Jun Zha, Feng Wu, Kaixuan Wei, Tao Zhang, Lizhi Wang, Ying Fu, Koushik Nagasubramanian, Asheesh K Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian
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 example-based 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.