MATLAB Implementation of Radon Transform for Motion Blur Processing

This article presents a motion blur processing method based on Radon transform. In image processing, motion blur represents a common challenge that can be effectively addressed using Radon transformation. The Radon transform is a mathematical operation that converts two-dimensional images into one-dimensional functions through line integration along various angles. By applying this transformation, we can better analyze blur patterns within images and perform restoration. The implementation typically involves MATLAB functions like radon() for forward transformation and iradon() for inverse reconstruction, with key parameters including theta (projection angles) and filter type selection. This paper demonstrates how to utilize the Radon transform-based motion blur processing approach, accompanied by comprehensive program explanations covering algorithm workflow, parameter optimization strategies, and practical usage instructions to help readers better understand and apply this methodology. The code structure includes image preprocessing, Radon projection calculation, blur parameter estimation, and inverse transformation for image restoration.