Edge Detection Algorithm Implemented Based on Anisotropic Diffusion
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Resource Overview
A MATLAB-based edge detection algorithm implemented on the foundation of anisotropic diffusion. Includes reference material (PDF format): "Scale-Space and Edge Detection Using Anisotropic Diffusion.pdf" from IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 12, NO. 7, JULY 1990. The implementation features PDE-based image smoothing with edge-preserving capabilities using diffusion coefficient functions.
Detailed Documentation
This is an edge detection algorithm implemented in MATLAB using anisotropic diffusion as its foundation. The algorithm implementation can be referenced through the following publication: "Scale-Space and Edge Detection Using Anisotropic Diffusion.pdf" from IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 12, NO. 7, JULY 1990. The paper details the fundamental principles and applications of edge detection algorithms.
The MATLAB implementation typically involves solving the Perona-Malik diffusion equation using finite difference methods, where key functions include calculating gradient magnitude for edge detection and implementing conduction coefficients that preserve edges while smoothing homogeneous regions. The code structure generally consists of iterative diffusion processes with controlled stopping criteria based on gradient thresholds or iteration counts.
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