Title :
Generalized Wiener reconstruction of images from colour sensor data using a scale invariant prior
Author_Institution :
New South Wales Univ., Sydney, NSW, Australia
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;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899577
