DocumentCode
2833210
Title
Generalized Wiener reconstruction of images from colour sensor data using a scale invariant prior
Author
Taubman, David
Author_Institution
New South Wales Univ., Sydney, NSW, Australia
Volume
3
fYear
2000
fDate
2000
Firstpage
801
Abstract
An algorithm is described for reconstructing images from colour sensor samples, which need not be aligned nor conform to a rectangular sampling geometry. The algorithm has applications in de-mosaicing digital camera color filter array (CFA) data, and processing other imaging modalities such as scanned images and captured video. A unique scale invariant WSS prior model is described for the uncorrupted surface spectral reflectance functions and used to form linear least mean squared error (LLMSE) optimal reconstructions with constrained support operators. Some important results are established concerning the existence and tractability of the solutions based on this prior
Keywords
Wiener filters; filtering theory; image colour analysis; image processing; image reconstruction; image sensors; least mean squares methods; optimisation; reflectivity; video cameras; video signal processing; LLMSE optimal reconstruction; Wiener filtering; algorithm; captured video; color filter array; colour sensor data; colour sensor samples; constrained support operators; digital camera CFA data de-mosaicing; generalized Wiener image reconstruction; linear least mean squared error; scale invariant WSS prior model; scale invariant prior; scanned images; surface spectral reflectance functions; Color; Digital cameras; Digital filters; Geometry; Image reconstruction; Image sampling; Image sensors; Reflectivity; Sensor phenomena and characterization; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location
Vancouver, BC
ISSN
1522-4880
Print_ISBN
0-7803-6297-7
Type
conf
DOI
10.1109/ICIP.2000.899577
Filename
899577
Link To Document