Preprint Article Version 1 This version not peer reviewed

Filter Selection for Optimizing Spectral Sensitivity of Broadband Multispectral Camera Based on Maximum Linear Independence

Version 1 : Received: 28 November 2017 / Approved: 29 November 2017 / Online: 29 November 2017 (15:03:07 CET)

How to cite: Li, S.; Xu, D.; Zhang, L..; Lin, J. Filter Selection for Optimizing Spectral Sensitivity of Broadband Multispectral Camera Based on Maximum Linear Independence. Preprints 2017, 2017110192 (doi: 10.20944/preprints201711.0192.v1). Li, S.; Xu, D.; Zhang, L..; Lin, J. Filter Selection for Optimizing Spectral Sensitivity of Broadband Multispectral Camera Based on Maximum Linear Independence. Preprints 2017, 2017110192 (doi: 10.20944/preprints201711.0192.v1).

Abstract

Previous research has shown that the effectiveness of selecting filter set from a large set of commercial broadband filters by vector analyzing method based on maximum linear independence (MLI). However, the traditional MLI is suboptimal due to predefining the first filter of the selected filter set being the maximum ℓ2 norm among all those of the filters. An exhaustive imaging simulation is conducted to investigate the features of the most competent filter set. In the simulation, every filter in a subset of all the filters is selected serving as the first filter in turn. From the results of the simulation, we found there are remarkable characteristics for the most competent filter set. Besides smaller condition number, the geometric features of the best-performed filter set comprise the distinct peak of the transmittance of the first filter, the generally uniform distributing of the peaks of the transmittance curve of the filters, the substantial overlapping of the transmittance curves with those of the adjacent filer sets. Therefore, the best-performed filter sets can be decided intuitively by simple vector analyzing and just a few experimental verifications. This work would be useful for optimizing spectral sensitivity of broadband multispectral imaging sensors or SFA sensors.

Subject Areas

spectral sensitivity optimization; filter selection; multispectral and hyperspectral imaging; absorption filters; imaging simulation; color reproduction; spectral reconstruction

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