Motion Blur Parameter Estimation

This document presents a MATLAB-based implementation for estimating blur direction in motion blur image restoration algorithms. Motion blur parameter estimation and direction calculation constitute critical steps in this restoration approach. To better understand the algorithm, let us first examine the fundamentals of motion blur and the necessity of image deblurring.

Motion blur represents a common image degradation type caused by relative motion between objects and the camera during exposure. When either the subject or camera moves, pixels undergo displacement, resulting in blurred image patterns. Restoring such images holds significant importance for various applications including image enhancement, object recognition, and computer vision systems.

The restoration process requires accurate estimation of both blur direction and motion parameters. Blur direction indicates the trajectory of relative motion between camera and subject, enabling precise image reconstruction. Motion parameters quantify velocity and displacement characteristics, allowing the algorithm to model the blur kernel mathematically. The implementation utilizes MATLAB's image processing toolbox for Fourier transform analysis and point spread function (PSF) modeling.

Our code implementation employs Radon transform techniques to detect dominant blur direction from the image's frequency domain characteristics. Key functions include: 1) Preprocessing module for image normalization, 2) Frequency analysis using 2D FFT to identify motion trails, 3) Direction estimation through angular spectrum analysis. The algorithm automatically calculates motion length parameters based on spectral zero-pattern recognition. Detailed code comments explain each processing stage, including PSF generation and Wiener filter implementation for final image restoration.

This implementation provides practical understanding of motion deblurring algorithms, featuring modular code structure suitable for integration into custom projects. The solution handles uniform linear motion blurs and includes validation metrics for restoration quality assessment.

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