Nonreference object-based pansharpening quality assessment
Pansharpening involves the fusion of panchromatic (PAN) and multispectral (MS) images to obtain a high-resolution image with enhanced spectral and spatial information. Assessing the quality of the resulting fused image poses a challenge due to the absence of a high-resolution reference image. Numero...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-06-01
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| Series: | Egyptian Journal of Remote Sensing and Space Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S111098232400022X |
| _version_ | 1797249165772718080 |
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| author | Shiva Aghapour Maleki Hassan Ghassemian Maryam Imani |
| author_facet | Shiva Aghapour Maleki Hassan Ghassemian Maryam Imani |
| author_sort | Shiva Aghapour Maleki |
| collection | DOAJ |
| description | Pansharpening involves the fusion of panchromatic (PAN) and multispectral (MS) images to obtain a high-resolution image with enhanced spectral and spatial information. Assessing the quality of the resulting fused image poses a challenge due to the absence of a high-resolution reference image. Numerous methods have been proposed to address this, from assessing quality at reduced resolution to full-resolution evaluations. Many existing approaches are pixel-based, where quality metrics are applied and averaged on individual pixels. In this article, we introduce a novel object-based method for assessing the quality of pansharpened images at full resolution. In object-based quality assessment methods, the reaction of different areas of the fused image to the fusion process is reflected. Our approach revolves around extracting objects from the given image and evaluating extracted objects. By doing so, the distinct responses of different objects within the fused image to the fusion process are captured. The proposed method leverages a unique object extraction technique known as segmentation by nearest neighbor (SNN) to extract objects of the MS image. This method extracts the objects based on the image’s characteristics without any requirement for parameter tuning. These extracted objects are then mapped onto both PAN and fused images. The proposed spectral index measures the spectral homogeneity of the fused image’s objects and the proposed spatial index measures the injected spatial content from the PAN image to the fused image’s objects. Experimental results underscore the robustness and reliability of the proposed method. Additionally, by visualizing distortion values on object-maps, we gain insights into fusion quality across diverse areas within the scene. |
| first_indexed | 2024-04-24T20:26:09Z |
| format | Article |
| id | doaj.art-b05f91b52894492e85e90f7207f29111 |
| institution | Directory Open Access Journal |
| issn | 1110-9823 |
| language | English |
| last_indexed | 2024-04-24T20:26:09Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Egyptian Journal of Remote Sensing and Space Sciences |
| spelling | doaj.art-b05f91b52894492e85e90f7207f291112024-03-22T05:38:49ZengElsevierEgyptian Journal of Remote Sensing and Space Sciences1110-98232024-06-01272227241Nonreference object-based pansharpening quality assessmentShiva Aghapour Maleki0Hassan Ghassemian1Maryam Imani2Image Processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, IranCorresponding author.; Image Processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, IranImage Processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, IranPansharpening involves the fusion of panchromatic (PAN) and multispectral (MS) images to obtain a high-resolution image with enhanced spectral and spatial information. Assessing the quality of the resulting fused image poses a challenge due to the absence of a high-resolution reference image. Numerous methods have been proposed to address this, from assessing quality at reduced resolution to full-resolution evaluations. Many existing approaches are pixel-based, where quality metrics are applied and averaged on individual pixels. In this article, we introduce a novel object-based method for assessing the quality of pansharpened images at full resolution. In object-based quality assessment methods, the reaction of different areas of the fused image to the fusion process is reflected. Our approach revolves around extracting objects from the given image and evaluating extracted objects. By doing so, the distinct responses of different objects within the fused image to the fusion process are captured. The proposed method leverages a unique object extraction technique known as segmentation by nearest neighbor (SNN) to extract objects of the MS image. This method extracts the objects based on the image’s characteristics without any requirement for parameter tuning. These extracted objects are then mapped onto both PAN and fused images. The proposed spectral index measures the spectral homogeneity of the fused image’s objects and the proposed spatial index measures the injected spatial content from the PAN image to the fused image’s objects. Experimental results underscore the robustness and reliability of the proposed method. Additionally, by visualizing distortion values on object-maps, we gain insights into fusion quality across diverse areas within the scene.http://www.sciencedirect.com/science/article/pii/S111098232400022XObject-based quality assessmentObject extractionPansharpeningSpatial indexSpectral index |
| spellingShingle | Shiva Aghapour Maleki Hassan Ghassemian Maryam Imani Nonreference object-based pansharpening quality assessment Egyptian Journal of Remote Sensing and Space Sciences Object-based quality assessment Object extraction Pansharpening Spatial index Spectral index |
| title | Nonreference object-based pansharpening quality assessment |
| title_full | Nonreference object-based pansharpening quality assessment |
| title_fullStr | Nonreference object-based pansharpening quality assessment |
| title_full_unstemmed | Nonreference object-based pansharpening quality assessment |
| title_short | Nonreference object-based pansharpening quality assessment |
| title_sort | nonreference object based pansharpening quality assessment |
| topic | Object-based quality assessment Object extraction Pansharpening Spatial index Spectral index |
| url | http://www.sciencedirect.com/science/article/pii/S111098232400022X |
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