Markov Random Field Image Segmentation MATLAB Source Code
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Resource Overview
MATLAB implementation of Markov Random Field-based image segmentation featuring ICM (Iterated Conditional Modes) algorithm for Maximum a Posteriori probability estimation, thoroughly tested and validated.
Detailed Documentation
This MATLAB source code implements image segmentation using Markov Random Fields with the Iterated Conditional Modes (ICM) algorithm to solve Maximum a Posteriori probability estimation. The implementation includes key functions for neighborhood system modeling, energy minimization, and label optimization through iterative conditional updates. The algorithm has been rigorously tested to ensure correctness and reliability, featuring proper handling of pixel dependencies and spatial constraints through pairwise potential functions. The code structure incorporates efficient matrix operations for Gibbs energy computation and systematic label propagation across image regions.
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