Nonuniform Defocus Removal for Image Classification

Understand

We propose and study the single-frame anisoplanatic deconvolution problem associated with image classification using machine learning algorithms, named the nonuniform defocus removal (NDR) problem.

• Mathematical analysis of the NDR problem is done and the so-called defocus removal (DR) algorithm for solving it is proposed.
• Global convergence of the DR algorithm is established without imposing any unverifiable assumption.
• Numerical results on simulation data show significant features of DR including solvability, noise robustness, convergence, model insensitivity and computational efficiency.