Institutional Repository of Radio Astronomy Research Laboratory
| CS-GAC: Compressively sensed geodesic active contours | |
Shan, Hao1,2
| |
| 2024-02-01 | |
| Source Publication | PATTERN RECOGNITION
 |
| ISSN | 0031-3203 |
| Volume | 146Pages:110007 |
| Contribution Rank | 1 |
| Abstract | This paper proposes an edge based compressively sensed (CS) geodesic active contour (GAC) model, termed CS-GAC, to ensure faithful edge detection and accurate object segmentation. The motivation behind this paper is that edge information driving the contour evolution can be iteratively obtained by incomplete CS measurements. In each iteration, the CS-GAC is a three-step process including edge detection, active contouring and sparse reconstruction. Instead of working on the final reconstructed images themselves, the evolution of the CS-GAC is driven by a few CS measurements and guided by updatable edge information. The edge information is generated by a complex shearlet transform (CST) based edge map. In the framework, reconstruction and edge detection work alternately. The iterative update property that takes advantages of both edge sparsity and edge detection can largely improve the evolution precision. Numerical experiments show that the CS-GAC can obtain challenging segmentation results in comparisons with the state of the art methods, and has competitive prospects. |
| Keyword | Compressed sensing/compressive sampling Geodesic active contours Edge detection Sparse reconstruction Image segmentation Level set Shearlet Curvelet Wavelet |
| DOI | 10.1016/j.patcog.2023.110007 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | IMAGE SEGMENTATION ; SNAKES ; MODEL ; INITIALIZATION ; RECONSTRUCTION ; FIELD |
| Funding Project | Special Projects of Major Science and Technology in Xinjiang Uygur Autonomous Region, China[2022A03013-4] ; NSFC[12373114] ; NSFC[12041304] ; NSFC[11673056] ; NSFC[11173042] ; China Scholarship Council, China[201409655001] ; Operation, Maintenance and Upgrading Fund for Astronomical Telescopes ; Ministry of Finance of China |
| WOS Research Area | Computer Science ; Engineering |
| WOS Subject | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS ID | WOS:001099691900001 |
| Publisher | ELSEVIER SCI LTD |
| Funding Organization | Special Projects of Major Science and Technology in Xinjiang Uygur Autonomous Region, China ; NSFC ; China Scholarship Council, China ; Operation, Maintenance and Upgrading Fund for Astronomical Telescopes ; Ministry of Finance of China |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.xao.ac.cn/handle/45760611-7/5590 |
| Collection | 射电天文研究室_行星科学研究团组 |
| Corresponding Author | Shan, Hao |
| Affiliation | 1.Chinese Acad Sci, Xinjiang Astron Observ, 150 Sci St 1st, Urumqi 830011, Xinjiang, Peoples R China 2.Chinese Acad Sci, Xinjiang Key Lab Radio Astrophys, 150 Sci St 1st, Urumqi 830011, Xinjiang, Peoples R China |
| Recommended Citation GB/T 7714 | Shan, Hao. CS-GAC: Compressively sensed geodesic active contours[J]. PATTERN RECOGNITION,2024,146:110007. |
| APA | Shan, Hao.(2024).CS-GAC: Compressively sensed geodesic active contours.PATTERN RECOGNITION,146,110007. |
| MLA | Shan, Hao."CS-GAC: Compressively sensed geodesic active contours".PATTERN RECOGNITION 146(2024):110007. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Shan-2024-CS-GAC_ Co（10773KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment