MATLAB Implementation of Radon Transform: Principles, Code Examples, and Applications

This document provides a concise introduction to the principles of Radon transform alongside practical examples to enhance understanding. However, theoretical knowledge alone is insufficient for real-world applications. We therefore present detailed implementation methodologies for Radon transform, covering specific procedural steps and practical implementation techniques. The implementation section includes discussions on algorithmic approaches such as the Fourier Slice Theorem and back-projection methods, with references to key MATLAB functions like radon() and iradon() for forward and inverse transformations. Additionally, we explore application domains where Radon transform proves valuable, including medical image processing (CT reconstruction) and non-destructive testing (defect detection). Through comprehensive examination of Radon transform's theoretical foundations, implementation strategies, and practical applications, readers will gain deeper insight into this technique's significance and utility in computational imaging.