Earlier work on blur identification suffers from using space-invariant image models to match space-variant (piecewise smooth) images. It is expected that an effective space-adaptive image model or estimate would improve the joint blur and image estimation. A well-known space-adaptive regularization method for image restoration is extended to solve this problem. The resulting scheme has two regularization terms, one for the image and the other for the blur. Very good performance is observed even though no stringent assumption about the structure of the underlying blur operator is made. The computational overhead for blur identification is less than the computational load required for regularized image restoration when the blur operator is exactly known.
|Original language||English (US)|
|Number of pages||5|
|Journal||Proceedings - International Conference on Image Processing, ICIP|
|State||Published - 1994|
|Event||Proceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA|
Duration: Nov 13 1994 → Nov 16 1994
Bibliographical noteFunding Information:
This work was supported by the BMDO/IST program managed by the Office of Naval Research under Contract N00014-92-J-1911
© 1994 IEEE.