Abstract
This paper considers the aspects of robust M-estimation in regularized image restoration. Robust functionals are employed to allow the representation and efficient suppression of a wide variety of noise processes and permit the reconstruction of sharp edges. A new class of robust entropic functionals is introduced, which operates only on the high-frequency content of the signal and reflects sharp deviations in the signal distribution. This class can also incorporate prior structural information regarding the original image, in a way similar to the maximum information principle. The properties of robust algorithms are demonstrated through restoration examples in different noise environments.
| Original language | English (US) |
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| Title of host publication | Image and Multidimensional Signal Processing |
| Publisher | Publ by IEEE |
| Volume | 5 |
| ISBN (Print) | 0780309464 |
| State | Published - Jan 1 1993 |
| Event | IEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) - Minneapolis, MN, USA Duration: Apr 27 1993 → Apr 30 1993 |
Other
| Other | IEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) |
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| City | Minneapolis, MN, USA |
| Period | 4/27/93 → 4/30/93 |