Please use this identifier to cite or link to this item:
https://idr.l1.nitk.ac.in/jspui/handle/123456789/8574Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Balaji, B. | |
| dc.contributor.author | Jidesh, P. | |
| dc.date.accessioned | 2020-03-30T10:22:26Z | - |
| dc.date.available | 2020-03-30T10:22:26Z | - |
| dc.date.issued | 2018 | |
| dc.identifier.citation | 2017 9th International Conference on Advances in Pattern Recognition, ICAPR 2017, 2018, Vol., , pp.187-192 | en_US |
| dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/8574 | - |
| dc.description.abstract | In this paper a non-local gradient vector flow model is designed for restoration of images corrupted with Gamma distributed (speckle) noise and linear blurring artefacts. The filter effectively preserves edges and finer details in the course of its evolution due to the presence of the non-local TV based diffusion term and the piecewise linear approximation is reduced considerably by the gradient fidelity term present in the model. The model is found suitable for restoration of various images from the field of satellite and clinical imaging. The experimental results are shown and compared for different image data sets both visually and qualitatively using various statistical measures. � 2017 IEEE. | en_US |
| dc.title | Non-local Gradient Fidelity Model for Multiplicative Gamma Noise Removal | en_US |
| dc.type | Book chapter | en_US |
| Appears in Collections: | 2. Conference Papers | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.