ASSESSING THE EFFECTIVENESS OF INPAINTING TECHNIQUES FOR ENHANCING FEATURE EXTRACTION QUALITY IN REMOTE SENSING IMAGERY

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorFontoura, C. F.M.-
Autor(es): dc.creatorCardim, G. P.-
Autor(es): dc.creatorNascimento, E. S.-
Autor(es): dc.creatorColnago, M.-
Autor(es): dc.creatorde, W. C.-
Autor(es): dc.creatorda Silva, E. A.-
Data de aceite: dc.date.accessioned2025-08-21T21:38:20Z-
Data de disponibilização: dc.date.available2025-08-21T21:38:20Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-12-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5194/isprs-annals-X-1-W1-2023-65-2023-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/304292-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/304292-
Descrição: dc.descriptionRemote Sensing (RS) images have been used in several applications of interest for society. Despite the precision and robustness derived from RS images, several aerial scenes exhibit imperfections and fall short of attaining ideal quality standards, as some of them present distortions such as noise, blur, and stripes. An alternative approach to deal with such distortions is by applying Inpainting techniques, however, under certain circumstances, this type of approach requires to be evaluated by quantitative metrics to assess the final quality of the reconstruction. Therefore, this paper focus on the issue of quantitatively evaluating inpainting results in the context of RS by analysing and comparing new evaluation metrics in contrast to the classical ones from the general literature of RS. More precisely, two inpainting techniques are applied for object removal and reconstruction of partially detected curvilinear cartographic features in RS images. Next, the obtained results are evaluated by taking six evaluation metrics to assess the agreement level between the metrics, as well as between qualitative evaluations conducted by human agents. Based on the evaluation of these metrics when applied to RS images, it can be concluded that the DISTS and VSI metrics are the most promising candidates for adaptation and application within the specific context of RS.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionFaculty of Science and Technology São Paulo State University - Unesp, Presidente Prudente Campus, Street Roberto Símonsen, 305, Pres. Prudente SP-
Descrição: dc.descriptionDepartment of Engineering Physics and Mathematics São Paulo State University - Unesp, Araraquara Campus, Av. Prof. Francisco Degni, 55, Jardim Quitandinha, SP-
Descrição: dc.descriptionFaculty of Engineering and Sciences Department of Engineering São Paulo State University - Unesp, Experimental Rosana Campus, Av. dos Barrageiros, 1881, SP-
Descrição: dc.descriptionInstitute of Biosciences Letters and Exact Sciences São Paulo State University - Unesp, São José do Rio Preto Campus, Street Cristóvão Colombo, 2265-
Descrição: dc.descriptionFaculty of Science and Technology São Paulo State University - Unesp, Presidente Prudente Campus, Street Roberto Símonsen, 305, Pres. Prudente SP-
Descrição: dc.descriptionDepartment of Engineering Physics and Mathematics São Paulo State University - Unesp, Araraquara Campus, Av. Prof. Francisco Degni, 55, Jardim Quitandinha, SP-
Descrição: dc.descriptionFaculty of Engineering and Sciences Department of Engineering São Paulo State University - Unesp, Experimental Rosana Campus, Av. dos Barrageiros, 1881, SP-
Descrição: dc.descriptionInstitute of Biosciences Letters and Exact Sciences São Paulo State University - Unesp, São José do Rio Preto Campus, Street Cristóvão Colombo, 2265-
Descrição: dc.descriptionCNPq: 2021/03328-3-
Descrição: dc.descriptionCNPq: 2021/12584-3-
Descrição: dc.descriptionCNPq: 2023/07543-1-
Descrição: dc.descriptionCNPq: 31622820214-
Descrição: dc.descriptionCNPq: 427915/2018-0-
Descrição: dc.descriptionCAPES: 88887.817761/2023-00-
Descrição: dc.descriptionCAPES: 88887.817769/2023-00-
Formato: dc.format65-72-
Idioma: dc.languageen-
Relação: dc.relationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectFeature Extraction-
Palavras-chave: dc.subjectInpainting-
Palavras-chave: dc.subjectMetrics-
Palavras-chave: dc.subjectQuantitative Analysis-
Palavras-chave: dc.subjectRemote Sensing-
Título: dc.titleASSESSING THE EFFECTIVENESS OF INPAINTING TECHNIQUES FOR ENHANCING FEATURE EXTRACTION QUALITY IN REMOTE SENSING IMAGERY-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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