Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria
Image segmentation plays a significant role in remote sensing image processing. Among numerous segmentation algorithms, the region-merging segmentation algorithm is widely used due to its well-organized structure and outstanding results. Many merging criteria (MC) were designed to improve the accura...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/14/2782 |
| _version_ | 1797526107734409216 |
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| author | Haoyu Wang Zhanfeng Shen Zihan Zhang Zeyu Xu Shuo Li Shuhui Jiao Yating Lei |
| author_facet | Haoyu Wang Zhanfeng Shen Zihan Zhang Zeyu Xu Shuo Li Shuhui Jiao Yating Lei |
| author_sort | Haoyu Wang |
| collection | DOAJ |
| description | Image segmentation plays a significant role in remote sensing image processing. Among numerous segmentation algorithms, the region-merging segmentation algorithm is widely used due to its well-organized structure and outstanding results. Many merging criteria (MC) were designed to improve the accuracy of region-merging segmentation, but each MC has its own shortcomings, which can cause segmentation errors. Segmentation accuracy can be improved by referring to the segmentation results. To achieve this, an approach for detecting and correcting region-merging image segmentation errors is proposed, and then an iterative optimization model is established. The main contributions of this paper are as follows: (1) The conflict types of matching segment pairs are divided into scale-expression conflict (SEC) and region-ownership conflict (ROC), and ROC is more suitable for optimization. (2) An equal-scale local evaluation method was designed to quantify the optimization potential of ROC. (3) A regional anchoring strategy is proposed to preserve the results of the previous iteration optimization. Three QuickBird satellite images of different land-cover types were used for validating the proposed approach. Both unsupervised and supervised evaluation results prove that the proposed approach can effectively improve segmentation accuracy. All explicit and implicit optimization modes are concluded, which further illustrate the stability of the proposed approach. |
| first_indexed | 2024-03-10T09:24:31Z |
| format | Article |
| id | doaj.art-36177fac6d934416bfb396279276379e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:24:31Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-36177fac6d934416bfb396279276379e2023-11-22T04:52:19ZengMDPI AGRemote Sensing2072-42922021-07-011314278210.3390/rs13142782Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging CriteriaHaoyu Wang0Zhanfeng Shen1Zihan Zhang2Zeyu Xu3Shuo Li4Shuhui Jiao5Yating Lei6National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaNational Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaBeijing Key Lab of Spatial Information Integration and 3S Application, Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing 100871, ChinaNational Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaNational Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaNational Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaNational Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaImage segmentation plays a significant role in remote sensing image processing. Among numerous segmentation algorithms, the region-merging segmentation algorithm is widely used due to its well-organized structure and outstanding results. Many merging criteria (MC) were designed to improve the accuracy of region-merging segmentation, but each MC has its own shortcomings, which can cause segmentation errors. Segmentation accuracy can be improved by referring to the segmentation results. To achieve this, an approach for detecting and correcting region-merging image segmentation errors is proposed, and then an iterative optimization model is established. The main contributions of this paper are as follows: (1) The conflict types of matching segment pairs are divided into scale-expression conflict (SEC) and region-ownership conflict (ROC), and ROC is more suitable for optimization. (2) An equal-scale local evaluation method was designed to quantify the optimization potential of ROC. (3) A regional anchoring strategy is proposed to preserve the results of the previous iteration optimization. Three QuickBird satellite images of different land-cover types were used for validating the proposed approach. Both unsupervised and supervised evaluation results prove that the proposed approach can effectively improve segmentation accuracy. All explicit and implicit optimization modes are concluded, which further illustrate the stability of the proposed approach.https://www.mdpi.com/2072-4292/13/14/2782image segmentationregion mergingsegmentation quality optimizationmerging criteria |
| spellingShingle | Haoyu Wang Zhanfeng Shen Zihan Zhang Zeyu Xu Shuo Li Shuhui Jiao Yating Lei Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria Remote Sensing image segmentation region merging segmentation quality optimization merging criteria |
| title | Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria |
| title_full | Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria |
| title_fullStr | Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria |
| title_full_unstemmed | Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria |
| title_short | Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria |
| title_sort | improvement of region merging image segmentation accuracy using multiple merging criteria |
| topic | image segmentation region merging segmentation quality optimization merging criteria |
| url | https://www.mdpi.com/2072-4292/13/14/2782 |
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