Edge detection in polarimetric synthetic aperture radar images using a hybrid approach based on scattering and statistical information
Extracting edge information is a major challenge for polarimetric synthetic aperture radar (PolSAR) image processing techniques, particularly when weak and robust edges emerge concurrently within urban areas. Despite their popularity, classic region-based PolSAR image edge detectors perform non-optimally in heterogeneous areas as the covariance matrix does not obey the Wishart distribution in such cases. To address this problem, a novel PolSAR edge detection algorithm that utilizes a change in the dominant scattering mechanism as a basis of edge detection is examined. An edge is assumed to exist whenever the dominant scattering mechanism for a given pixel is different from its neighboring pixels. Because solid edges/outer boundaries of homogeneous areas are better identified by the classical filtering-based method, its fusion with the proposed algorithm is used to retain the best edge information. The performance of the suggested technique is assessed using two real PolSAR datasets and compared with state-of-the-art techniques. The results demonstrate that the proposed method is more accurate in identifying and preserving the edges corresponding to different ground objects/structures.
Authors
- Himanshu Maurya (ORCID: https://orcid.org/0000-0002-6043-4156)
- Rakesh Sharma (ORCID: https://orcid.org/0000-0001-9444-5665)
- Rajib Kumar Panigrahi (ORCID: https://orcid.org/0000-0002-8920-0492)
- Inderkumar Kochar
- Amit Kumar (ORCID: https://orcid.org/0000-0001-7180-2500)
Institutions
- Indian Institute of Technology Roorkee (IN)
- Indian Institute of Information Technology Allahabad (IN)
- National Institute of Technology Hamirpur (BD)
Publication Details
- Journal
- Journal of Applied Remote Sensing
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1117/1.jrs.18.034519
- Citations
- 1
- Primary Topic
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.30