Direct Reconstruction of Distorted Signals and Images Using Shifts Methods
Abstract
Mathematical methods of step-by-step and combined shifts are proposed for experimental data processing to reconstruct the measuring system impulse response distorted by shift-invariant blur. Proposed methods base on direct non-blind deconvolution without using approximations and integral transforms. Methods are fast and effective for accurate data reconstruction, which gives a possibility of increasing the effective resolution of measuring systems by mathematical methods up to physical limits without solving the expensive and quite difficult scientific and technical problems. Step-by-step and combined shifts methods supplement each other in data reconstruction at different distortions of signals, noise levels and data volumes. Methods may be adapted for reconstruction of multi-dimensional data. There are considered the restorations of 2D images blurred by uniform motion and distorted by functions, which may be factored, such as Gaussian-like functions. The comparative analysis of step-by-step and combined shifts methods is presented. Reconstruction inaccuracies are estimated. Examples of signal reconstructions and image restorations at different distortions are considered.
Keywords
Cite
@article{arxiv.1901.07953,
title = {Direct Reconstruction of Distorted Signals and Images Using Shifts Methods},
author = {Andrey V. Novikov-Borodin},
journal= {arXiv preprint arXiv:1901.07953},
year = {2019}
}
Comments
Submitted to IEEE Trans on Signal Processing, 14-Jan-2019