Ma, J., Chan, J. C.-W., & Canters, F. (2014). Robust locally weighted regression for supperresolution enhancement of multi-angle remote sensing imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(4), 1357-1371.

@article{adbc22081c8a43298bf0d1ffb3d88822,
title = "Robust locally weighted regression for supperresolution enhancement of multi-angle remote sensing imagery",
abstract = "This paper presents a robust locally weighted least-squares kernel regression method for superresolution (SR) enhancement of multi-angle remote sensing imagery. The method is based on the concept of kernel-based regression, where the local image patch is approximated by an mbiN-term Taylor series. To reduce the impact of high frequency noise on SR performance, a robust fitting procedure is adopted. The approach proposed is tested with simulated multi-angle data derived from panchromatic WorldView-2 imagery and with real multi-angle WorldView-2 remote sensing images.",
keywords = "Superresolution, multi-angle images",
author = "Jianglin Ma and Chan, {Jonathan Cheung-Wai} and Frank Canters",
year = "2014",
month = apr,
day = "22",
language = "English",
volume = "7",
pages = "1357--1371",
journal = "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing",
issn = "1939-1404",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",
}