A Nash-game approach to Blind Image Deblurring
Nora Nasr, N. Moussaid, Omar Gouasnouane · 2021
Images are undeniably a vital part in our life, they are now used in all of kind of fields, hence, image processing became a must. Common image processing include image enhancement, restoration, encoding, and compression. Restoring is a process to improve an degraded image quality, to sharpen an image, and remove the noise. A major cause of image degradation is blur. There are many types of blur: motion blur, the most common, is a blur due to subject movement, or a camera shake. Blind deconvolution is the reconstruction of a sharp clean version of a blurred image without prior knowledge of the blur kernel (PSF) or the original image. In this paper, we will study the Nash game as a blind deconvolution technique for image deblurring, and we will test this method by presenting some numerical examples, and comparing it with other methods predefined in MATLAB, or existing in the literature.