Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing
Abstract In the field of image processing, tangling noise and artefacts elimination of objects are two essential tasks. Tangling noise and lack of intensity in certain applications also occur at the same time. In this paper, a new variational model is proposed based on total variation and l0 the nor...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-05-01
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| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ell2.12148 |
| _version_ | 1798003145007169536 |
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| author | Muhammad Ashfaq Khan Fayaz Ali Dharejo Farah Deeba Shahzad Ashraf Juntae Kim Hoon Kim |
| author_facet | Muhammad Ashfaq Khan Fayaz Ali Dharejo Farah Deeba Shahzad Ashraf Juntae Kim Hoon Kim |
| author_sort | Muhammad Ashfaq Khan |
| collection | DOAJ |
| description | Abstract In the field of image processing, tangling noise and artefacts elimination of objects are two essential tasks. Tangling noise and lack of intensity in certain applications also occur at the same time. In this paper, a new variational model is proposed based on total variation and l0 the norm for simultaneously removing the tangling noise, estimating the location of missing pixels, and filling in them. To be specific, the total variation is used to regularize the estimated image and use the l0 norm to make the missing pixel to be sparse. Moreover, the data fidelity term is given by a new forward description about the degraded process and the gamma noise assumption. Finally, an algorithm based on the alternating direction multiplier method is exploited to solve the model. By conducting simulated and real experiments, the damaged images can be effectively restored by the proposed method. In qualitative and quantitative terms, this approach works better. |
| first_indexed | 2024-04-11T12:03:03Z |
| format | Article |
| id | doaj.art-92829cb5ca7d46f4a4be6a73ce79be7a |
| institution | Directory Open Access Journal |
| issn | 0013-5194 1350-911X |
| language | English |
| last_indexed | 2024-04-11T12:03:03Z |
| publishDate | 2021-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Electronics Letters |
| spelling | doaj.art-92829cb5ca7d46f4a4be6a73ce79be7a2022-12-22T04:24:48ZengWileyElectronics Letters0013-51941350-911X2021-05-01571143643810.1049/ell2.12148Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processingMuhammad Ashfaq Khan0Fayaz Ali Dharejo1Farah Deeba2Shahzad Ashraf3Juntae Kim4Hoon Kim5Department of Computer Engineering Dongguk University Seoul South KoreaInstitute of Computer Network Information Center, Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing 100190 ChinaInstitute of Computer Network Information Center, Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing 100190 ChinaCollege of Internet of Things Engineering, Hohai University Changzhou Jiangsu ChinaDepartment of Computer Engineering Dongguk University Seoul South KoreaIoT and Big‐Data Research Center, Department of Electronics Engineering Incheon National University Incheon 22012 South KoreaAbstract In the field of image processing, tangling noise and artefacts elimination of objects are two essential tasks. Tangling noise and lack of intensity in certain applications also occur at the same time. In this paper, a new variational model is proposed based on total variation and l0 the norm for simultaneously removing the tangling noise, estimating the location of missing pixels, and filling in them. To be specific, the total variation is used to regularize the estimated image and use the l0 norm to make the missing pixel to be sparse. Moreover, the data fidelity term is given by a new forward description about the degraded process and the gamma noise assumption. Finally, an algorithm based on the alternating direction multiplier method is exploited to solve the model. By conducting simulated and real experiments, the damaged images can be effectively restored by the proposed method. In qualitative and quantitative terms, this approach works better.https://doi.org/10.1049/ell2.12148Optical, image and video signal processingComputer vision and image processing techniques |
| spellingShingle | Muhammad Ashfaq Khan Fayaz Ali Dharejo Farah Deeba Shahzad Ashraf Juntae Kim Hoon Kim Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing Electronics Letters Optical, image and video signal processing Computer vision and image processing techniques |
| title | Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing |
| title_full | Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing |
| title_fullStr | Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing |
| title_full_unstemmed | Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing |
| title_short | Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing |
| title_sort | toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing |
| topic | Optical, image and video signal processing Computer vision and image processing techniques |
| url | https://doi.org/10.1049/ell2.12148 |
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