Small-kernel, constrained least-squares restoration of sampled image dataFollowing the work of Park (1989), who extended a derivation of the Wiener filter based on the incomplete discrete/discrete model to a more comprehensive end-to-end continuous/discrete/continuous model, it is shown that a derivation of the constrained least-squares (CLS) filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model. This results in an improved CLS restoration filter, which can be efficiently implemented as a small-kernel convolution in the spatial domain.
Hazra, Rajeeb (Lockheed Engineering & Sciences Co.; NASA, Langley Research Center Hampton, VA, United States)
Park, Stephen K. (College of William and Mary Williamsburg, VA, United States)
August 16, 2013
January 1, 1992
Publication: In: Visual information processing; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992 (A93-32438 12-61)
COMPUTER PROGRAMMING AND SOFTWARE
IDRelationTitle19930048441Analytic PrimaryVisual information processing; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992visibility_off