Hosseinzadeh, S. A Fuzzy Inference System for Unsupervised Deblurring of Motion Blur in Electron Beam Calibration. Appl. Syst. Innov.2018, 1, 48.
Hosseinzadeh, S. A Fuzzy Inference System for Unsupervised Deblurring of Motion Blur in Electron Beam Calibration. Appl. Syst. Innov. 2018, 1, 48.
Hosseinzadeh, S. A Fuzzy Inference System for Unsupervised Deblurring of Motion Blur in Electron Beam Calibration. Appl. Syst. Innov.2018, 1, 48.
Hosseinzadeh, S. A Fuzzy Inference System for Unsupervised Deblurring of Motion Blur in Electron Beam Calibration. Appl. Syst. Innov. 2018, 1, 48.
Abstract
This paper presents a novel method of restoring the electron beam (EB) measurements that are degraded by linear motion blur. This is based on a Fuzzy Inference System (FIS) and Wiener inverse filter, together providing autonomy, reliability, flexibility and real-time execution. This system is capable of restoring highly degraded signals without requiring the exact knowledge of EB probe size. The FIS is formed of three inputs, eight fuzzy rules and one output. The FIS is responsible to monitor the restoration results, grade their validity and choose the one that yields to a better grade. These grades are produced autonomously by analyzing results of Wiener inverse filter. To benchmark the performance of the system, ground truth signals obtained using an 18 um wire probe are compared with the restorations. Main aims are therefore a) Provide unsupervised deblurring for device independent EB measurement; b) Improve the reliability of the process; c) Apply deblurring without knowing the probe size. These, further facilitates the deployment and manufacturing of EB probes and probe independent and accurate EB characterization. It also makes restoration of previously collected EB measurements easier, where the probe sizes are not known or recorded.
Keywords
fuzzy inference system; fuzzy logics; linear motion blur; fuzzy debluring; electron beam calibration; signal & image processing
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
