Proposes a general form of the weighted smoothing functional for regularized image restoration. The weighting matrices which introduce the spatial adaptivity are defined as a function of the (partially) restored image. As a result no prior knowledge about the image is required but the smoothing functional to be minimized is nonlinear with respect to the unknown image. Conditions for the convexity of the functional are established. An iterative algorithm is proposed for obtaining its minimum. Sufficient conditions for the convergence of the algorithm are established. Various forms of the weighting matrices are proposed. Experimental results demonstrate the effectiveness of the approach.
|Number of pages||5|
|Journal||Proceedings - International Conference on Image Processing, ICIP|
|Publication status||Published - 1994|
|Event||Proceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA|
Duration: 1994 Nov 13 → 1994 Nov 16
Bibliographical notePublisher Copyright:
© 1994 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Signal Processing