| 1. Identity statement | |||||||
| Reference Type | Conference Paper (Conference Proceedings) | ||||||
| Site | sibgrapi.sid.inpe.br | ||||||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | ||||||
| Identifier | 8JMKD3MGPEW34M/438DG7H | ||||||
| Repository | sid.inpe.br/sibgrapi/2020/09.11.16.10 | ||||||
| Last Update | 2020:10.01.19.25.59 (UTC) administrator | ||||||
| Metadata Repository | sid.inpe.br/sibgrapi/2020/09.11.16.10.02 | ||||||
| Metadata Last Update | 2022:06.14.00.00.02 (UTC) administrator | ||||||
| DOI | 10.1109/SIBGRAPI51738.2020.00022 | ||||||
| Citation Key | PiresSanSanSanPap:2020:ImDeUs | ||||||
| Title | Image Denoising using Attention-Residual Convolutional Neural Networks  | ||||||
| Format | On-line | ||||||
| Year | 2020 | ||||||
| Access Date | 2024, Sep. 19 | ||||||
| Number of Files | 1 | ||||||
| Size | 1980 KiB | ||||||
| 2. Context | |||||||
| Author | 1 Pires, Rafael Gonçalves 2 Santos, Daniel Felipe Silva 3 Santana, Marcos Cleison Silva 4 Santos, Claudio Filipe Gonçalves dos 5 Papa, João Paulo | ||||||
| Affiliation | 1 São Paulo State University (UNESP) 2 São Paulo State University (UNESP) 3 São Paulo State University (UNESP) 4 Federal University of São Carlos (UFSCAR) 5 São Paulo State University (UNESP) | ||||||
| Editor | Musse, Soraia Raupp Cesar Junior, Roberto Marcondes Pelechano, Nuria Wang, Zhangyang (Atlas) | ||||||
| e-Mail Address | rafapires@gmail.com | ||||||
| Conference Name | Conference on Graphics, Patterns and Images, 33 (SIBGRAPI) | ||||||
| Conference Location | Porto de Galinhas (virtual) | ||||||
| Date | 7-10 Nov. 2020 | ||||||
| Publisher | IEEE Computer Society | ||||||
| Publisher City | Los Alamitos | ||||||
| Book Title | Proceedings | ||||||
| Tertiary Type | Full Paper | ||||||
| History (UTC) | 2020-10-01 19:25:59 :: rafapires@gmail.com -> administrator :: 2020 2022-06-14 00:00:02 :: administrator -> rafapires@gmail.com :: 2020 | ||||||
| 3. Content and structure | |||||||
| Is the master or a copy? | is the master | ||||||
| Content Stage | completed | ||||||
| Transferable | 1 | ||||||
| Version Type | finaldraft | ||||||
| Keywords | image restoration deep learning | ||||||
| Abstract | During the image acquisition process, noise is usually added to the data mainly due to physical limitations of the acquisition sensor, and also regarding imprecisions during the data transmission and manipulation. In that sense, the resultant image needs to be processed to attenuate its noise without losing details. Non-learning-based strategies such as filter-based and noise prior modeling have been adopted to solve the image denoising problem. Nowadays, learning-based denoising techniques showed to be much more effective and flexible approaches, suchas Residual Convolutional Neural Networks. Here, we propose a new learning-based non-blind denoising technique named Attention Residual Convolutional Neural Network (ARCNN), and its extension to blind denoising named Flexible Attention Residual Convolutional Neural Network (FARCNN). The proposed methods try to learn the underlying noise expectation using an Attention-Residual mechanism. Experiments on public datasets corrupted by different levels of Gaussian and Poisson noise support the effectiveness of the proposed approaches against some state-of-the-art image denoising methods. ARCNN achieved an overall average PSNR results of around 0.44dB and 0.96dB for Gaussian and Poisson denoising, respectively FARCNN presented very consistent results, even with slightly worsen performance compared to ARCNN. | ||||||
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2020 > Image Denoising using... | ||||||
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Image Denoising using... | ||||||
| doc Directory Content | access | ||||||
| source Directory Content |
| ||||||
| agreement Directory Content |
| ||||||
| 4. Conditions of access and use | |||||||
| data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/438DG7H | ||||||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/438DG7H | ||||||
| Language | en | ||||||
| Target File | PID6634881.pdf | ||||||
| User Group | rafapires@gmail.com | ||||||
| Visibility | shown | ||||||
| Update Permission | not transferred | ||||||
| 5. Allied materials | |||||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | ||||||
| Next Higher Units | 8JMKD3MGPEW34M/43G4L9S 8JMKD3MGPEW34M/4742MCS | ||||||
| Citing Item List | sid.inpe.br/sibgrapi/2020/10.28.20.46 27 sid.inpe.br/sibgrapi/2022/06.10.21.49 2 | ||||||
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 | ||||||
| 6. Notes | |||||||
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume | ||||||
| 7. Description control | |||||||
| e-Mail (login) | rafapires@gmail.com | ||||||
| update | |||||||