Restoration of images degraded by atmospheric turbulence by a least-squares method and a Markov process.

We present a two-step deconvolution method for restoring images degraded by atmospheric turbulence. The first step is linear space-invariant filtering, and the second step is a nonhomogeneous Markov process. This nonhomogeneous method preserves the discontinuities of the original image better than the homogeneous method does.

Optimality of trade-off filters.

We compare the optimal trade-off approach for synthetic discriminant function filters and an approach introduced recently, the minimum noise and correlation energy filter, using an objective quantitative figure of merit. A new general definition of multicriteria optimal trade-off correlation filters is introduced based on this comparison.