3D Shape Reconstruction MATLAB Code with Shape-from-Defocus and Diffusion Techniques
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Resource Overview
This MATLAB implementation performs 3D shape reconstruction using shape-from-defocus methodology combined with diffusion processing. The algorithm enables complete 3D reconstruction from just two differently-focused images, significantly simplifying data acquisition while maintaining reconstruction accuracy through sophisticated depth-from-defocus calculations and diffusion-based noise reduction.
Detailed Documentation
This MATLAB code implements 3D shape reconstruction utilizing shape-from-defocus principles enhanced with diffusion techniques. The core algorithm calculates depth information by analyzing the blur differences between two images captured at different focal distances. Key implementation features include Gaussian point spread function modeling for defocus simulation, gradient-based diffusion equations for surface smoothing, and iterative optimization for depth map refinement. The method significantly streamlines data collection requirements while delivering efficient shape reconstruction through advanced image processing techniques that handle optical blur characteristics and preserve surface continuity.
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