Improved Generalized IHS Based on Total Variation for Pansharpening
Pansharpening refers to the fusion of a panchromatic (PAN) and a multispectral (MS) image aimed at generating a high-quality outcome over the same area. This particular image fusion problem has been widely studied, but until recently, it has been challenging to balance the spatial and spectral fidel...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/11/2945 |
| _version_ | 1827739244716621824 |
|---|---|
| author | Xuefeng Zhang Xiaobing Dai Xuemin Zhang Yuchen Hu Yingdong Kang Guang Jin |
| author_facet | Xuefeng Zhang Xiaobing Dai Xuemin Zhang Yuchen Hu Yingdong Kang Guang Jin |
| author_sort | Xuefeng Zhang |
| collection | DOAJ |
| description | Pansharpening refers to the fusion of a panchromatic (PAN) and a multispectral (MS) image aimed at generating a high-quality outcome over the same area. This particular image fusion problem has been widely studied, but until recently, it has been challenging to balance the spatial and spectral fidelity in fused images. The spectral distortion is widespread in the component substitution-based approaches due to the variation in the intensity distribution of spatial components. We lightened the idea using the total variation optimization to improve upon a novel GIHS-TV framework for pansharpening. The framework drew the high spatial fidelity from the GIHS scheme and implemented it with a simpler variational expression. An improved L1-TV constraint to the new spatial–spectral information was introduced to the GIHS-TV framework, along with its fast implementation. The objective function was solved by the Iteratively Reweighted Norm (IRN) method. The experimental results on the “PAirMax” dataset clearly indicated that GIHS-TV could effectively reduce the spectral distortion in the process of component substitution. Our method has achieved excellent results in visual effects and evaluation metrics. |
| first_indexed | 2024-03-11T02:58:05Z |
| format | Article |
| id | doaj.art-d5ae3dd35cc5476da84a883b8984d8ca |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T02:58:05Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d5ae3dd35cc5476da84a883b8984d8ca2023-11-18T08:30:51ZengMDPI AGRemote Sensing2072-42922023-06-011511294510.3390/rs15112945Improved Generalized IHS Based on Total Variation for PansharpeningXuefeng Zhang0Xiaobing Dai1Xuemin Zhang2Yuchen Hu3Yingdong Kang4Guang Jin5School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaPansharpening refers to the fusion of a panchromatic (PAN) and a multispectral (MS) image aimed at generating a high-quality outcome over the same area. This particular image fusion problem has been widely studied, but until recently, it has been challenging to balance the spatial and spectral fidelity in fused images. The spectral distortion is widespread in the component substitution-based approaches due to the variation in the intensity distribution of spatial components. We lightened the idea using the total variation optimization to improve upon a novel GIHS-TV framework for pansharpening. The framework drew the high spatial fidelity from the GIHS scheme and implemented it with a simpler variational expression. An improved L1-TV constraint to the new spatial–spectral information was introduced to the GIHS-TV framework, along with its fast implementation. The objective function was solved by the Iteratively Reweighted Norm (IRN) method. The experimental results on the “PAirMax” dataset clearly indicated that GIHS-TV could effectively reduce the spectral distortion in the process of component substitution. Our method has achieved excellent results in visual effects and evaluation metrics.https://www.mdpi.com/2072-4292/15/11/2945pansharpeningGIHStotal variation |
| spellingShingle | Xuefeng Zhang Xiaobing Dai Xuemin Zhang Yuchen Hu Yingdong Kang Guang Jin Improved Generalized IHS Based on Total Variation for Pansharpening Remote Sensing pansharpening GIHS total variation |
| title | Improved Generalized IHS Based on Total Variation for Pansharpening |
| title_full | Improved Generalized IHS Based on Total Variation for Pansharpening |
| title_fullStr | Improved Generalized IHS Based on Total Variation for Pansharpening |
| title_full_unstemmed | Improved Generalized IHS Based on Total Variation for Pansharpening |
| title_short | Improved Generalized IHS Based on Total Variation for Pansharpening |
| title_sort | improved generalized ihs based on total variation for pansharpening |
| topic | pansharpening GIHS total variation |
| url | https://www.mdpi.com/2072-4292/15/11/2945 |
| work_keys_str_mv | AT xuefengzhang improvedgeneralizedihsbasedontotalvariationforpansharpening AT xiaobingdai improvedgeneralizedihsbasedontotalvariationforpansharpening AT xueminzhang improvedgeneralizedihsbasedontotalvariationforpansharpening AT yuchenhu improvedgeneralizedihsbasedontotalvariationforpansharpening AT yingdongkang improvedgeneralizedihsbasedontotalvariationforpansharpening AT guangjin improvedgeneralizedihsbasedontotalvariationforpansharpening |