Abstract
We consider the adaptive restoration of inhomogeneous textured images degraded by linear blur and additive white Gaussian noise (AWGN) . The method consists of segmenting the image into individual homogeneous textures and restoring each texture separately. The individual textures are assumed to be realizations of 2-D Wold-decomposition based regular, homogeneous random fields which may possess deterministic components. The conventional Wiener filter assumes that the spectral distribution of the signal is absolutely continuous and therefore, cannot be directly used to restore the individual textures. A generalized Wiener filter accommodates the unified texture model and is shown to yield minimum mean-squared error (MMSE) estimates for fields with discontinuous spectral distributions. Texture discrimination is performed by obtaining maximum a posieriori (MAP) estimates for the label field using simulated annealing. The performance of our segmentation algorithm is investigated in the presence of noise.
Original language | English |
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Pages (from-to) | 261-268 |
Number of pages | 8 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 2094 |
DOIs | |
State | Published - 1 Dec 1993 |
Externally published | Yes |
Event | Visual Communications and Image Processing 1993 - Cambridge, MA, United States Duration: 7 Nov 1993 → 7 Nov 1993 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering