Spectral image reconstruction using an edge preserving spatio-spectral Wiener estimation
JOSA A, Vol. 26, Issue 8, pp. 1865-1875 (2009)
http://dx.doi.org/10.1364/JOSAA.26.001865
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Abstract
Reconstruction of spectral images from camera responses is investigated using an edge preserving spatio-spectral Wiener estimation. A Wiener denoising filter and a spectral reconstruction Wiener filter are combined into a single spatio-spectral filter using local propagation of the noise covariance matrix. To preserve edges the local mean and covariance matrix of camera responses is estimated by bilateral weighting of neighboring pixels. We derive the edge-preserving spatio-spectral Wiener estimation by means of Bayesian inference and show that it fades into the standard Wiener reflectance estimation shifted by a constant reflectance in case of vanishing noise. Simulation experiments conducted on a six-channel camera system and on multispectral test images show the performance of the filter, especially for edge regions. A test implementation of the method is provided as a MATLAB script at the first author’s website.
© 2009 Optical Society of America
OCIS Codes
(100.2000) Image processing : Digital image processing
(100.3010) Image processing : Image reconstruction techniques
(330.1690) Vision, color, and visual optics : Color
(110.4234) Imaging systems : Multispectral and hyperspectral imaging
ToC Category:
Image Processing
History
Original Manuscript: March 3, 2009
Revised Manuscript: June 22, 2009
Manuscript Accepted: June 26, 2009
Published: July 29, 2009
Virtual Issues
Vol. 4, Iss. 10 Virtual Journal for Biomedical Optics
Citation
Philipp Urban, Mitchell R. Rosen, and Roy S. Berns, "Spectral image reconstruction using an edge preserving spatio-spectral Wiener estimation," J. Opt. Soc. Am. A 26, 1865-1875 (2009)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-26-8-1865
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