Blind restoration of atmospherically degraded images by automatic best step-edge detection

Image restoration algorithms often require previous knowledge about the point spread function (PSF) of the disturbance. Deriving the PSF manually from a degraded ideal step-edge in the image is a well known procedure intended mainly for isotropic degradations. A common image degradation that can be approximated as isotropic is the atmospheric blurring in long-distance imaging. This paper proposes an efficient method that automatically finds the best (closest to ideal) step-edge from the degraded image. The identified PSF is then used to restore the image. The existence of a good step-edge in the image may be assumed in cases such as imaging of urban areas, which is common in applications such as visual surveillance and reconnaissance. The criteria employed include the straightness and length of the edge, its strength, and the homogeneity of the step. An efficient algorithm is proposed, and results of automatic blind image restoration based on the automatically extracted PSF are shown.

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