Name
Title | ||
|---|---|---|
Neural Network-Based Image Restoration Using Scaled Residual With Space-Variant Regularization |
Abstract | ||
|---|---|---|
Image restoration is aimed to recover the original scene from its degraded version. This paper presents a new method for image restoration. In this technique, an evaluation function which combines a scaled residual with space-variant regularization is established and minimized using a Hopfield network to obtain a restored image from a noise corrupted and blurred image. Simulation results demonstrate that the proposed evaluation function leads to a more efficient restoration process which offers a fast convergence and improved restored image quality. (C) 2003 Wiley Periodicals, Inc. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1002/ima.10034 | INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY |
Keywords | Field | DocType |
image restoration, neural network, regularization techniques, adaptive processing | Convergence (routing),Residual,Computer vision,Computer science,Image quality,Evaluation function,Regularization (mathematics),Artificial intelligence,Image restoration,Artificial neural network,Hopfield network | Journal |
Volume | Issue | ISSN |
12 | 6 | 0899-9457 |
Citations | PageRank | References |
1 | 0.38 | 12 |
Authors | ||
2 | ||