Abstract
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.
Original language | English (US) |
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Article number | 413660 |
Pages (from-to) | 695-699 |
Number of pages | 5 |
Journal | Proceedings - International Conference on Image Processing, ICIP |
Volume | 2 |
DOIs | |
State | Published - 1994 |
Event | The 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA Duration: Nov 13 1994 → Nov 16 1994 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing