Abstract

In singular vector space produced by singular value decomposition, the effect of noise on the expansion coefficients of an object is clear. A new image restoration method estimates the expansion coefficients corrupted by noise from the expansion coefficients corresponding to large singular values by incorporating a priori information about the noise and the object. This information can be described as closed convex sets. Iterative projections onto the convex sets are performed to obtain a restored image. The effectiveness of the method in singular vector space is made clear through computer simulations for 2-D bandlimited degraded images.

© 1987 Optical Society of America

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