Improving the iterative back projection estimation through Lorentzian sharp infinite symmetrical filter

Autor: Amir Nazren Abdul Rahim, Shahrul Nizam Yaakob, Lee Yeng Seng, Mohd Wafi Nasrudin, Iszaidy Ismail
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Electrical and Computer Engineering (IJECE). 12:2539
ISSN: 2722-2578
2088-8708
DOI: 10.11591/ijece.v12i3.pp2539-2552
Popis: This study proposed an enhancement technique for improvising the estimation technique in iterative back projection (IBP) by using the Lorentzian error function with a sharp infinite symmetrical filter (SISEF). The IBP estimation is an iteratively based error correction that can minimize the error reconstruction significantly. However, the IBP has a drawback in that it suffers from jaggy and ringing artifacts as a result of the iterative reconstruction method and the absence of edge guidance. Furthermore, because the IBP estimator tended to oscillate at the same solution frequently, numerous iterations were required. Therefore, this study proposed edge enhancement to enhance the estimator by using the combination of the IBP with Lorentzian SISEF to produce a finer high-resolution output image. As a result, the SISEF is used to improvise the estimator by providing high accuracy of edge detail information for enhancing the edge image. At the same time, the Lorentzian error norm helps to increase the robustness of the IBP algorithm from contamination of additional noise and the ringing artifacts.
Databáze: OpenAIRE