+ Site Statistics
+ Search Articles
+ Subscribe to Site Feeds
EurekaMag Most Shared ContentMost Shared
EurekaMag PDF Full Text ContentPDF Full Text
+ PDF Full Text
Request PDF Full TextRequest PDF Full Text
+ Follow Us
Follow on FacebookFollow on Facebook
Follow on TwitterFollow on Twitter
Follow on LinkedInFollow on LinkedIn

+ Translate

RBFN restoration of nonlinearly degraded images

RBFN restoration of nonlinearly degraded images

IEEE Transactions on Image Processing 5(6): 964-975

We investigate a technique for image restoration using nonlinear networks based on radial basis functions. The technique is also based on the concept of training or learning by examples. When trained properly, these networks are used as spatially invariant feedforward nonlinear filters that can perform restoration of images degraded by nonlinear degradation mechanisms. We examine a number of network structures including the Gaussian radial basis function network (RBFN) and some extensions of it, as well as a number of training algorithms including the stochastic gradient (SG) algorithm that we have proposed earlier. We also propose a modified structure based on the Gaussian-mixture model and a learning algorithm for the modified network. Experimental results indicate that the radial basis function network and its extensions can be very useful in restoring images degraded by nonlinear distortion and noise.

(PDF emailed within 0-6 h: $19.90)

Accession: 055333638

Download citation: RISBibTeXText

PMID: 18285184

DOI: 10.1109/83.503912

Related references

Artificial neural networks for blur identification and restoration of nonlinearly degraded images. International Journal of Neural Systems 11(5): 455-461, 2001

Restoration of turbulence-degraded images by the most-common method. Applied Optics 30(27): 3924-3929, 1991

Restoration of color images degraded by chromatic aberrations. Applied Optics 19(22): 3869-3876, 1980

Restoration of moving binary images degraded owing to phosphor persistence. Applied Optics 30(26): 3734-3739, 1991

Space-variant restoration of images degraded by camera motion blur. IEEE Transactions on Image Processing 17(2): 105-116, 2008

Restoration of degraded images by composite gratings in a coherent optical processor. Applied Optics 12(7): 1703-1712, 1973

Supervised restoration of degraded medical images using multiple-point geostatistics. Computer Methods and Programs in Biomedicine 106(3): 201-209, 2012

Restoration of images degraded by atmospheric turbulence by a least-squares method and a Markov process. Optics Letters 21(6): 423-425, 1996

Restoration of images degraded by spatially varying pointspread functions by a conjugate gradient method. Applied Optics 17(14): 2186-2190, 1978

Combined homomorphic and local-statistics processing for restoration of images degraded by signal-dependent noise. Applied Optics 23(6): 845-845, 1984

Restoration of images degraded by underwater turbulence using structure tensor oriented image quality (STOIQ) metric. Optics Express 23(13): 17077-17090, 2015

Real-time restoration of images degraded by uniform motion blur in foveal active vision systems. IEEE Transactions on Image Processing 8(12): 1838-1842, 2008

A field theoretical restoration method for images degraded by non-uniform light attenuation : an application for light microscopy. Optics Express 17(14): 11294-11308, 2009

Restoration of sustainability of physically degraded fish habitats: The Model of Intermediate Restoration. Ecohydrology & Hydrobiology 1(3): 279-282, 2001

Selection of pollution-tolerant trees for restoration of degraded forests and evaluation of the experimental restoration practices at. 2008