MATLAB Implementation of 1D to 3D Algorithms with Multi-Shape Scatterer Examples

This documentation presents algorithms for dimensional transformation from 1D to 3D, incorporating examples of multiple scatterer shapes. These algorithms are implemented through MATLAB programs utilizing numerical computation methods such as discrete Fourier transforms and spatial interpolation techniques. The implementation efficiently simulates various real-world scenarios through optimized matrix operations and parallel computing capabilities. For instance, in medical imaging applications, these algorithms enable accurate 3D reconstruction of internal human structures using back-projection methods and regularization techniques. In industrial applications, they facilitate detection and identification of scatterer shapes and sizes through advanced pattern recognition algorithms and boundary detection functions. Additionally, these algorithms find applications in communications systems using beamforming techniques and geological exploration through subsurface imaging methods, providing researchers with a powerful computational toolkit featuring modular code architecture and customizable parameters for different scattering models.