In this paper the general form of adaptive image restoration algorithms is derived. The adaptivity of the algorithm is introduced by the constraint operator which incorporates properties of the response of the human visual system. The properties of the visual system are represented by noise masking and visibility functions. Based on the values of the visibility function the image is divided into classes with similar spatial activity. Then, a regularization technique with a different regularization parameter is applied to each class. The proposed algorithms are general and can be used for any type of linear constraint and distortion operators. The algorithms can also be used to restore signals different than images, since the constraint operator can be interpreted as adapting to the local signal activity.
|Original language||English (US)|
|Number of pages||5|
|State||Published - Dec 1 1986|
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