@InProceedings{CosmoInabSall:2017:SiImSu,
author = "Cosmo, Daniel Luis and Inaba, Fernando Kentaro and Salles, Evandro
Ottoni Teatini",
affiliation = "UFES and UFES and UFES",
title = "Single Image Super-Resolution Using Multiple Extreme Learning
Machine Regressors",
booktitle = "Proceedings...",
year = "2017",
editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and
Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and
Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba,
Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo
and Vital, Creto and Pagot, Christian Azambuja and Petronetto,
Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "Super-Resolution, Extreme Learning Machine.",
abstract = "This paper presents a new technique to solve the single image
super resolution reconstruction problem based on multiple extreme
learning machine regressors, called here MELM. The MELM employs a
feature space of low resolution images, divided in subspaces, and
one regressor is trained for each one. In the training task, we
employ a color dataset containing 91 images, with approximately
5.3 million pixels, and PSNR and SSIM as metric evaluation. For
the experiments we use two datasets, Set 5 and Set 14, to evaluate
the results. We observe MELM improves reconstruction quality in
about 0.44 dB PSNR in average for Set 5, when compared with a
global ELM regressor (GELM), trained for the entire feature space.
The proposed method almost reaches deep learning reconstruction
quality, without depending on large datasets and long training
times, giving a competitive trade off between performance and
computational costs.",
conference-location = "Niter{\'o}i, RJ, Brazil",
conference-year = "17-20 Oct. 2017",
doi = "10.1109/SIBGRAPI.2017.59",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2017.59",
language = "en",
ibi = "8JMKD3MGPAW/3PFQSB8",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3PFQSB8",
targetfile = "PID4960161.pdf",
urlaccessdate = "2024, Apr. 29"
}