An Improved SIFT Underwater Image Stitching Method
Underwater image stitching is a technique employed to seamlessly merge images with overlapping regions, creating a coherent underwater panorama. In recent years, extensive research efforts have been devoted to advancing image stitching methodologies for both terrestrial and underwater applications....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/22/12251 |
| _version_ | 1827640697214205952 |
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| author | Haosu Zhang Ruohan Zheng Wenrui Zhang Jinxin Shao Jianming Miao |
| author_facet | Haosu Zhang Ruohan Zheng Wenrui Zhang Jinxin Shao Jianming Miao |
| author_sort | Haosu Zhang |
| collection | DOAJ |
| description | Underwater image stitching is a technique employed to seamlessly merge images with overlapping regions, creating a coherent underwater panorama. In recent years, extensive research efforts have been devoted to advancing image stitching methodologies for both terrestrial and underwater applications. However, existing image stitching methods, which do not utilize detector information, heavily rely on matching feature pairs and tend to underperform in situations where underwater images contain regions with blurred feature textures. To address this challenge, we present an improved scale-invariant feature transform (SIFT) underwater image stitching method. This method enables the stitching of underwater images with arbitrarily acquired images featuring blurred feature contours and that do not require any detector information. Specifically, we perform a coarse feature extraction between the reference and training images, and then we acquire the target image and perform an accurate feature extraction between the reference and target images. In the final stage, we propose an improved fade-in and fade-out fusion method to obtain a panoramic underwater image. The experimental results show that our proposed method demonstrates enhanced robustness, particularly in scenarios where detecting feature points is challenging, when compared to traditional SIFT methods. Additionally, our method achieves higher matching accuracy and produces higher-quality results in the stitching of underwater images. |
| first_indexed | 2024-03-09T17:03:16Z |
| format | Article |
| id | doaj.art-2b123680736f4572a7dff67aff449328 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T17:03:16Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2b123680736f4572a7dff67aff4493282023-11-24T14:26:51ZengMDPI AGApplied Sciences2076-34172023-11-0113221225110.3390/app132212251An Improved SIFT Underwater Image Stitching MethodHaosu Zhang0Ruohan Zheng1Wenrui Zhang2Jinxin Shao3Jianming Miao4Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai 519000, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai 519000, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai 519000, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai 519000, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai 519000, ChinaUnderwater image stitching is a technique employed to seamlessly merge images with overlapping regions, creating a coherent underwater panorama. In recent years, extensive research efforts have been devoted to advancing image stitching methodologies for both terrestrial and underwater applications. However, existing image stitching methods, which do not utilize detector information, heavily rely on matching feature pairs and tend to underperform in situations where underwater images contain regions with blurred feature textures. To address this challenge, we present an improved scale-invariant feature transform (SIFT) underwater image stitching method. This method enables the stitching of underwater images with arbitrarily acquired images featuring blurred feature contours and that do not require any detector information. Specifically, we perform a coarse feature extraction between the reference and training images, and then we acquire the target image and perform an accurate feature extraction between the reference and target images. In the final stage, we propose an improved fade-in and fade-out fusion method to obtain a panoramic underwater image. The experimental results show that our proposed method demonstrates enhanced robustness, particularly in scenarios where detecting feature points is challenging, when compared to traditional SIFT methods. Additionally, our method achieves higher matching accuracy and produces higher-quality results in the stitching of underwater images.https://www.mdpi.com/2076-3417/13/22/12251SIFTimage stitchingimage alignmentimage preprocessingpoint matching |
| spellingShingle | Haosu Zhang Ruohan Zheng Wenrui Zhang Jinxin Shao Jianming Miao An Improved SIFT Underwater Image Stitching Method Applied Sciences SIFT image stitching image alignment image preprocessing point matching |
| title | An Improved SIFT Underwater Image Stitching Method |
| title_full | An Improved SIFT Underwater Image Stitching Method |
| title_fullStr | An Improved SIFT Underwater Image Stitching Method |
| title_full_unstemmed | An Improved SIFT Underwater Image Stitching Method |
| title_short | An Improved SIFT Underwater Image Stitching Method |
| title_sort | improved sift underwater image stitching method |
| topic | SIFT image stitching image alignment image preprocessing point matching |
| url | https://www.mdpi.com/2076-3417/13/22/12251 |
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