Filter Selection for Hyperspectral Estimation

Boaz Arad, Ohad Ben-Shahar; The IEEE International Conference on Computer Vision (ICCV), 2017, pp. 3153-3161


While recovery of hyperspectral signals from natural RGB images has been a recent subject of exploration, little to no consideration has been given to the camera response profiles used in the recovery process. In this paper we demonstrate that optimal selection of camera response filters may improve hyperspectral estimation accuracy by over 33%, emphasizing the importance of considering and selecting these response profiles wisely. Additionally, we present an evolutionary optimization methodology for optimal filter set selection from very large filter spaces, an approach that facilitates practical selection from families of customizable filters or filter optimization for multispectral cameras with more than 3 channels.

Related Material

author = {Arad, Boaz and Ben-Shahar, Ohad},
title = {Filter Selection for Hyperspectral Estimation},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {Oct},
year = {2017}