Distortion operator kernel and accuracy of iterative image restoration

Artyom Makovetskii; Vitaly Kober

doi:10.1117/12.2059898

23 September 2014 Distortion operator kernel and accuracy of iterative image restoration

Artyom Makovetskii, Vitaly Kober

Proceedings Volume 9217, Applications of Digital Image Processing XXXVII; 921705 (2014) https://doi.org/10.1117/12.2059898
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

Variational functionals are commonly used for restoration of images distorted by a linear operator. In order to minimize a functional, the gradient descent method can be used. In this paper, we analyze the performance of the gradient descent method in the frequency domain and show that the method converges to the sum of the original undistorted function and the kernel function of a linear distortion operator. For uniform linear degradation, the kernel function is oscillating. It is shown that the use of metrical as well as topological characteristics can improve restoration quality. Computer simulation results are provided to illustrate the performance of the proposed algorithm.

Citation Download Citation

Artyom Makovetskii and Vitaly Kober "Distortion operator kernel and accuracy of iterative image restoration", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921705 (23 September 2014); https://doi.org/10.1117/12.2059898

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