WMFLICM: A Robust Algorithm for SAR Image Segmentation Using Hybrid Spatial Information

ABSTRACT

Synthetic aperture RADAR (SAR) imaging is an important means for performing the task of remote sensing. Image segmentation is one of the most crucial steps done prior to the classification and identification of different regions and objects present in the acquired images. The presence of multiplicative speckle noise in SAR images makes the tasks of image processing extremely challenging. The fuzzy C-means (FCM) segmentation technique and its variants perform satisfactorily for images corrupted by additive noise, but these algorithms and other intensity-based conventional methods do not show encouraging results in case of speckle-contaminated SAR images. Segmentation performance for SAR images can be improved by incorporating spatial context information. Also, heavily contaminated SAR images cannot be effectively processed based on the intensity feature alone. Image textural features prove to be robust and more appropriate for the purpose of segmentation of SAR images. Hence a hybrid methodology, Weighted Membership Fuzzy Local Information C-Means (WMFLICM), is proposed in this research work, which uses spatial context information by incorporating both implicit and explicit neighbourhood information in terms of feature similarity in local window. In the proposed method, wavelet energy based feature is used to represent the textural information for the images generated by SAR sensors. Experiments conducted on synthetic as well as real SAR images demonstrate that the proposed algorithm with enhanced spatial information is more effective than other methods used for segmentation of SAR images.

Keywords:

• FCM
• Segmentation
• Spatial information
• Speckle
• Synthetic aperture radar
• Wavelet energy

Additional information

Notes on contributors

Pratibha Singh Jaiswal

Pratibha Singh Jaiswal received the BTech degree in electronics and communication engineering from Jamia Millia Islamia, Delhi, India, in 2005. She is currently pursuing MTech in signal processing and digital design from the Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India. Her areas of interest include machine vision, image processing, and remote sensing.

Mahipal Singh Choudhry

Mahipal Singh Choudhry received both bachelor's and master's degrees in the field of electronics & communication engineering from Malviya Regional Engineering College, now Malviya National Institute of Technology, Jaipur, India. He obtained his PhD from Delhi Technological University, Delhi. At present, he is working as professor in the Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India. He is a member of professional societies such as IEEE, IETE, and ISTE. He has published papers in international, national journals of repute, and conferences. His research interests include digital image processing and biomedical signal processing. Email: [email protected]