Image restoration in singular vector space by the method of convex projections.
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.
Sasaki
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Yamagami
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