Blind Restoration of Motion-Blurred Images with Unknown Motion Direction

Blind restoration of motion-blurred images with unknown motion direction presents a challenging computational task. This process requires addressing two primary technical aspects: pixel displacement and motion angle estimation. First, the algorithm must identify and localize displaced pixels within the blurred image, then restore them to their original positions using techniques such as inverse filtering or Wiener filter implementation. Second, the motion angle must be accurately determined through methods like Radon transform or cepstrum analysis to properly model the point spread function (PSF) for effective deblurring. These operations demand precise algorithmic approaches, potentially involving optimization techniques like maximum likelihood estimation or blind deconvolution algorithms (e.g., Richardson-Lucy deconvolution) to handle the ill-posed nature of the problem. Consequently, blind restoration of motion-blurred images with unknown parameters constitutes a complex research domain requiring sophisticated computational methods and innovative approaches for robust solution implementation.