Spectrum Correction Using Modeled Panchromatic Image for Pansharpening
Pansharpening is a method applied for the generation of high-spatial-resolution multi-spectral (MS) images using panchromatic (PAN) and multi-spectral images. A common challenge in pansharpening is to reduce the spectral distortion caused by increasing the resolution. In this paper, we propose a met...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Journal of Imaging |
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| Online Access: | https://www.mdpi.com/2313-433X/6/4/20 |
| _version_ | 1797571319619911680 |
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| author | Naoko Tsukamoto Yoshihiro Sugaya Shinichiro Omachi |
| author_facet | Naoko Tsukamoto Yoshihiro Sugaya Shinichiro Omachi |
| author_sort | Naoko Tsukamoto |
| collection | DOAJ |
| description | Pansharpening is a method applied for the generation of high-spatial-resolution multi-spectral (MS) images using panchromatic (PAN) and multi-spectral images. A common challenge in pansharpening is to reduce the spectral distortion caused by increasing the resolution. In this paper, we propose a method for reducing the spectral distortion based on the intensity–hue–saturation (IHS) method targeting satellite images. The IHS method improves the resolution of an RGB image by replacing the intensity of the low-resolution RGB image with that of the high-resolution PAN image. The spectral characteristics of the PAN and MS images are different, and this difference may cause spectral distortion in the pansharpened image. Although many solutions for reducing spectral distortion using a modeled spectrum have been proposed, the quality of the outcomes obtained by these approaches depends on the image dataset. In the proposed technique, we model a low-spatial-resolution PAN image according to a relative spectral response graph, and then the corrected intensity is calculated using the model and the observed dataset. Experiments were conducted on three IKONOS datasets, and the results were evaluated using some major quality metrics. This quantitative evaluation demonstrated the stability of the pansharpened images and the effectiveness of the proposed method. |
| first_indexed | 2024-03-10T20:38:39Z |
| format | Article |
| id | doaj.art-409daa5827544e2e8f75f0da61f09096 |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-10T20:38:39Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-409daa5827544e2e8f75f0da61f090962023-11-19T20:49:56ZengMDPI AGJournal of Imaging2313-433X2020-04-01642010.3390/jimaging6040020Spectrum Correction Using Modeled Panchromatic Image for PansharpeningNaoko Tsukamoto0Yoshihiro Sugaya1Shinichiro Omachi2Graduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, JapanGraduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, JapanGraduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, JapanPansharpening is a method applied for the generation of high-spatial-resolution multi-spectral (MS) images using panchromatic (PAN) and multi-spectral images. A common challenge in pansharpening is to reduce the spectral distortion caused by increasing the resolution. In this paper, we propose a method for reducing the spectral distortion based on the intensity–hue–saturation (IHS) method targeting satellite images. The IHS method improves the resolution of an RGB image by replacing the intensity of the low-resolution RGB image with that of the high-resolution PAN image. The spectral characteristics of the PAN and MS images are different, and this difference may cause spectral distortion in the pansharpened image. Although many solutions for reducing spectral distortion using a modeled spectrum have been proposed, the quality of the outcomes obtained by these approaches depends on the image dataset. In the proposed technique, we model a low-spatial-resolution PAN image according to a relative spectral response graph, and then the corrected intensity is calculated using the model and the observed dataset. Experiments were conducted on three IKONOS datasets, and the results were evaluated using some major quality metrics. This quantitative evaluation demonstrated the stability of the pansharpened images and the effectiveness of the proposed method.https://www.mdpi.com/2313-433X/6/4/20pansharpeningspectrum correctionintensity correctionmodelrelative spectral response graphIKONOS |
| spellingShingle | Naoko Tsukamoto Yoshihiro Sugaya Shinichiro Omachi Spectrum Correction Using Modeled Panchromatic Image for Pansharpening Journal of Imaging pansharpening spectrum correction intensity correction model relative spectral response graph IKONOS |
| title | Spectrum Correction Using Modeled Panchromatic Image for Pansharpening |
| title_full | Spectrum Correction Using Modeled Panchromatic Image for Pansharpening |
| title_fullStr | Spectrum Correction Using Modeled Panchromatic Image for Pansharpening |
| title_full_unstemmed | Spectrum Correction Using Modeled Panchromatic Image for Pansharpening |
| title_short | Spectrum Correction Using Modeled Panchromatic Image for Pansharpening |
| title_sort | spectrum correction using modeled panchromatic image for pansharpening |
| topic | pansharpening spectrum correction intensity correction model relative spectral response graph IKONOS |
| url | https://www.mdpi.com/2313-433X/6/4/20 |
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