Multispectral image restoration with multisensors

Abstract

A procedure is advanced to restore a single color image, which has been degraded by a linear shift-invariant blur in the presence of additive stationary noise. Four sensors are needed, followed by the application of the RGB-to-YIQ transformation. Subsequently, one three-dimensional (3D) Wiener filter on a sequence of two luminance component images and two two-dimensional (2D) Wiener filters on each of the two chrominance component images are needed. For the procedure to be successful, the imposition of a strongly coprime condition on the wavenumber response of two distinct sensor blur functions is necessary. The resulting well-conditioned problem is shown to provide improved restoration over the decorrelated component and the independent channel restoration methods, each of which uses one sensor for each of the three primary color components.