Automatic Identification of Motion Blur Length in MATLAB

In this article, we explore how to implement automatic identification of motion blur length using MATLAB. Motion blur occurs when objects move relative to the camera during exposure time. This type of blur can be reduced through image processing algorithms to enhance image clarity. We will demonstrate MATLAB-based algorithms for detecting motion blur length and performing automatic identification based on the results. The implementation typically involves analyzing the frequency domain characteristics using Fourier transforms, where motion blur appears as distinct directional patterns. Key MATLAB functions like fft2(), ifft2(), and radon transform are often employed to measure blur parameters. By implementing edge detection and Hough transform techniques, the algorithm can automatically determine the blur direction and length. This method enables more accurate determination of motion blur parameters in images, leading to better processing and restoration of motion-blurred images through deconvolution approaches like Wiener filtering or Lucy-Richardson algorithm.