SAR Image Segmentation Using ICM Method Based on MRF Field

This document presents an implementation of SAR image segmentation using the Iterated Conditional Modes (ICM) method based on Markov Random Field (MRF) modeling. The ICM algorithm operates on maximum a posteriori (MAP) estimation principles, performing image segmentation through iterative pixel label updates. In our implementation, we employ MRF to model spatial dependencies between pixels, which significantly enhances segmentation accuracy and stability. The core algorithm involves initializing pixel labels, then iteratively updating each pixel's label by maximizing the conditional probability given its neighborhood configuration. Through the ICM approach, we effectively partition SAR images into distinct target regions, facilitating better understanding and analysis of image content. Key implementation aspects include defining the energy function that combines data fidelity terms with spatial smoothness constraints, and setting convergence criteria for the iterative optimization process.