Adaptive Active Contour Model Based on Weighted RBPF for SAR Image Segmentation

We propose a new adaptive active contour model (ACM) based on weighted region-based pressure force (RBPF) which is applied to SAR image segmentation. First, the normalized intra-class variances of pixel grayscales of inner and outer areas are used as the new coefficients of the grayscale descriptions of inner and outer areas. Then, the weighted RBPF is constructed to control the curve motion more accurately. Second, when calculating the grayscale descriptions of the inner and outer areas, adaptive weights are introduced to reduce the effect of interference pixels, which improves the accuracy of the grayscale descriptions. Furthermore, some regularized terms are incorporated into the objective functional to ensure the stability of the model. The segmentation results for various kinds of images demonstrate that the proposed model is superior to some state-of-the-art ACMs in segmentation performance and is robust to the initial curve.