Edge and Texture Information-Based Fuzzy Active Contour For SAR Image Segmentation
Shiyu Luo, Ling Tong · 2024
Recently a novel active contour model referred to as fuzzy-based active contour model embedded with edge detector shows its good performance in the segmentation of images, however, it cannot be applied to Synthetic Aperture Radar (SAR) images directly due to speckle noise. In this model, the edge detector is not suited to detect boundary and the used intensity average information cannot distinguish different regions in SAR images. To this end, this paper proposes a modified fuzzy active contour model that incorporates edge and texture information for SAR image segmentation. First, number of false alarm defined in the improved line segment detector is modified as edge detection operator. Second, texture information obtained based on the textural image attained by Gabor filter is used instead of intensity average information. Third, edge and texture information obtained by the abovementioned operators is embedded in the energy functional related to the fuzzy active contour model and the segmentation is then achieved by minimizing this functional using a numerical iteration process. In the experiment, the segmentation results qualitative and quantitative validate the effectiveness of the proposed model.