Paper
26 February 2019 A comparative study of methods and algorithms for spatially resolved spectral value reconstruction with multispectral resolving filter-on-chip CMOS sensors
Author Affiliations +
Abstract
Mosaic filter-on-chip CMOS sensors enable the parallel acquisition of spatial and spectral information. These mosaic sensors are characterized by spectral filters which are applied directly on the sensor pixel in a matrix which is multiplied in the x- and y-direction over the entire sensor surface. Current mosaic sensors for the visible wavelength area using 9 or 16 different spectral filters in 3 × 3 or 4 × 4 matrices. Methods for the reconstruction of spectral reflectance from multispectral resolving sensors have been developed. It is known that the spectral reflectance of natural objects can be approximated with a limited number of spectral base functions. Therefore, continuous spectral distributions can be reconstructed from multispectral data of a limited number of channels. This paper shows how continuous spectral distributions can be reconstructed using spectral reconstruction methods like Moore-Penrose pseudo-inverse, Wiener estimation, Polynomial reconstruction and Reverse principal component analysis. These methods will be evaluated with monolithic mosaic sensors. The Goodness of Fit Coefficient and the CIE color difference are used to evaluate the reconstruction results. The reconstruction methods and the spectral base functions applied for the mosaic sensors are juxtaposed and practical conclusions are drawn for their application.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P.-G. Dittrich, L. Radtke, C. Zhang, S. Guo, B. Buch, M. Rosenberger, and G. Notni "A comparative study of methods and algorithms for spatially resolved spectral value reconstruction with multispectral resolving filter-on-chip CMOS sensors", Proc. SPIE 10912, Physics and Simulation of Optoelectronic Devices XXVII, 109120Z (26 February 2019); https://doi.org/10.1117/12.2507789
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Principal component analysis

Optical filters

Calibration

Cameras

CMOS sensors

Reflectivity

Back to Top