Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative
The Perona-Malik (PM) model is used successfully in image processing to eliminate noise while preserving edges; however, this model has a major drawback: it tends to make the image look blocky. This work proposes to modify the PM model by introducing the Caputo-Fabrizio fractional gradient inside th...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2020/7624829 |
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| _version_ | 1832554096363569152 |
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| author | Gustavo Asumu Mboro Nchama Angela Leon Mecias Mariano Rodriguez Ricard |
| author_facet | Gustavo Asumu Mboro Nchama Angela Leon Mecias Mariano Rodriguez Ricard |
| author_sort | Gustavo Asumu Mboro Nchama |
| collection | DOAJ |
| description | The Perona-Malik (PM) model is used successfully in image processing to eliminate noise while preserving edges; however, this model has a major drawback: it tends to make the image look blocky. This work proposes to modify the PM model by introducing the Caputo-Fabrizio fractional gradient inside the diffusivity function. Experiments with natural images show that our model can suppress efficiently the blocky effect. Also, our model has good performance in visual quality, high peak signal-to-noise ratio (PSNR), and lower value of mean absolute error (MAE) and mean square error (MSE). |
| format | Article |
| id | doaj-art-8423e23dae3748f9adac3e07d74ca3da |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-8423e23dae3748f9adac3e07d74ca3da2025-02-03T05:52:29ZengWileyAbstract and Applied Analysis1085-33751687-04092020-01-01202010.1155/2020/76248297624829Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio DerivativeGustavo Asumu Mboro Nchama0Angela Leon Mecias1Mariano Rodriguez Ricard2Universidad Nacional de Guinea Ecuatorial (UNGE), Malabo, GuineaUniversidad Nacional de Guinea Ecuatorial (UNGE), Malabo, GuineaUniversidad Nacional de Guinea Ecuatorial (UNGE), Malabo, GuineaThe Perona-Malik (PM) model is used successfully in image processing to eliminate noise while preserving edges; however, this model has a major drawback: it tends to make the image look blocky. This work proposes to modify the PM model by introducing the Caputo-Fabrizio fractional gradient inside the diffusivity function. Experiments with natural images show that our model can suppress efficiently the blocky effect. Also, our model has good performance in visual quality, high peak signal-to-noise ratio (PSNR), and lower value of mean absolute error (MAE) and mean square error (MSE).http://dx.doi.org/10.1155/2020/7624829 |
| spellingShingle | Gustavo Asumu Mboro Nchama Angela Leon Mecias Mariano Rodriguez Ricard Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative Abstract and Applied Analysis |
| title | Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative |
| title_full | Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative |
| title_fullStr | Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative |
| title_full_unstemmed | Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative |
| title_short | Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative |
| title_sort | perona malik model with diffusion coefficient depending on fractional gradient via caputo fabrizio derivative |
| url | http://dx.doi.org/10.1155/2020/7624829 |
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