Selecting change image for efficient change detection
Abstract Change detection (CD) is a fundamental problem that aims at detecting changed objects from two observations. Previous CNN‐based CD methods detect changes through multi‐scale deep convolutional features extracted from two images. However, we find that change always occurs in the ‘Query’ imag...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-05-01
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| Series: | IET Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/sil2.12095 |
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| _version_ | 1850166207019220992 |
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| author | Rui Huang Ruofei Wang Yuxiang Zhang Yan Xing Wei Fan Kai Leung Yung |
| author_facet | Rui Huang Ruofei Wang Yuxiang Zhang Yan Xing Wei Fan Kai Leung Yung |
| author_sort | Rui Huang |
| collection | DOAJ |
| description | Abstract Change detection (CD) is a fundamental problem that aims at detecting changed objects from two observations. Previous CNN‐based CD methods detect changes through multi‐scale deep convolutional features extracted from two images. However, we find that change always occurs in the ‘Query’ image for fixed cameras. This condition means that changes can be detected in advance from a single image with a coarse change. In this paper, we propose an efficient CD method to detect precise changes from the change image. First, a change image selector is designed to identify the image containing changes. Second, a coarse change prior map generator is proposed to generate coarse change prior to indicate the position of changes. Then, we introduce a simple multi‐scale CD module to refine the coarse change detection. As only one image is used in the multi‐scale CD module, our method is more efficient in training and testing than other compared methods. Numerous experiments have been conducted to analyse the effectiveness of the proposed method. Experimental results show that the proposed method achieves superior detection performance and higher speed than other compared CD methods. |
| format | Article |
| id | doaj-art-dda35e6a88f8422cbb9fdf7fdb4cf45a |
| institution | OA Journals |
| issn | 1751-9675 1751-9683 |
| language | English |
| publishDate | 2022-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj-art-dda35e6a88f8422cbb9fdf7fdb4cf45a2025-08-20T02:21:30ZengWileyIET Signal Processing1751-96751751-96832022-05-0116332733910.1049/sil2.12095Selecting change image for efficient change detectionRui Huang0Ruofei Wang1Yuxiang Zhang2Yan Xing3Wei Fan4Kai Leung Yung5College of Computer Science and Technology Civil Aviation University of China Tianjin ChinaCollege of Computer Science and Technology Civil Aviation University of China Tianjin ChinaCollege of Computer Science and Technology Civil Aviation University of China Tianjin ChinaCollege of Computer Science and Technology Civil Aviation University of China Tianjin ChinaCollege of Computer Science and Technology Civil Aviation University of China Tianjin ChinaDepartment of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Hong KongAbstract Change detection (CD) is a fundamental problem that aims at detecting changed objects from two observations. Previous CNN‐based CD methods detect changes through multi‐scale deep convolutional features extracted from two images. However, we find that change always occurs in the ‘Query’ image for fixed cameras. This condition means that changes can be detected in advance from a single image with a coarse change. In this paper, we propose an efficient CD method to detect precise changes from the change image. First, a change image selector is designed to identify the image containing changes. Second, a coarse change prior map generator is proposed to generate coarse change prior to indicate the position of changes. Then, we introduce a simple multi‐scale CD module to refine the coarse change detection. As only one image is used in the multi‐scale CD module, our method is more efficient in training and testing than other compared methods. Numerous experiments have been conducted to analyse the effectiveness of the proposed method. Experimental results show that the proposed method achieves superior detection performance and higher speed than other compared CD methods.https://doi.org/10.1049/sil2.12095change detectionchange image selectorefficient change detectionmulti‐scale change detection |
| spellingShingle | Rui Huang Ruofei Wang Yuxiang Zhang Yan Xing Wei Fan Kai Leung Yung Selecting change image for efficient change detection IET Signal Processing change detection change image selector efficient change detection multi‐scale change detection |
| title | Selecting change image for efficient change detection |
| title_full | Selecting change image for efficient change detection |
| title_fullStr | Selecting change image for efficient change detection |
| title_full_unstemmed | Selecting change image for efficient change detection |
| title_short | Selecting change image for efficient change detection |
| title_sort | selecting change image for efficient change detection |
| topic | change detection change image selector efficient change detection multi‐scale change detection |
| url | https://doi.org/10.1049/sil2.12095 |
| work_keys_str_mv | AT ruihuang selectingchangeimageforefficientchangedetection AT ruofeiwang selectingchangeimageforefficientchangedetection AT yuxiangzhang selectingchangeimageforefficientchangedetection AT yanxing selectingchangeimageforefficientchangedetection AT weifan selectingchangeimageforefficientchangedetection AT kaileungyung selectingchangeimageforefficientchangedetection |