Quality Assessment of Images Transmitted over Optical Fiber Communications Systems based on Statistical Metrics
Ghanem, H., El-Shafai, W., El-Rabaie, E., Mohamed, A., Rashed, A., Abd El-Samie, F., Tabbour, M. (2019). Quality Assessment of Images Transmitted over Optical Fiber Communications Systems based on Statistical Metrics. EKB Journal Management System, 28(2), 287-304. doi: 10.21608/mjeer.2019.62791
Hanan Ghanem; Walid El-Shafai; El-Sayed El-Rabaie; Abd Naser Mohamed; Ahmed Rashed; Fathi Abd El-Samie; Mohammed Tabbour. "Quality Assessment of Images Transmitted over Optical Fiber Communications Systems based on Statistical Metrics". EKB Journal Management System, 28, 2, 2019, 287-304. doi: 10.21608/mjeer.2019.62791
Ghanem, H., El-Shafai, W., El-Rabaie, E., Mohamed, A., Rashed, A., Abd El-Samie, F., Tabbour, M. (2019). 'Quality Assessment of Images Transmitted over Optical Fiber Communications Systems based on Statistical Metrics', EKB Journal Management System, 28(2), pp. 287-304. doi: 10.21608/mjeer.2019.62791
Ghanem, H., El-Shafai, W., El-Rabaie, E., Mohamed, A., Rashed, A., Abd El-Samie, F., Tabbour, M. Quality Assessment of Images Transmitted over Optical Fiber Communications Systems based on Statistical Metrics. EKB Journal Management System, 2019; 28(2): 287-304. doi: 10.21608/mjeer.2019.62791

Quality Assessment of Images Transmitted over Optical Fiber Communications Systems based on Statistical Metrics

Menoufia Journal of Electronic Engineering Research
Article 16, Volume 28, Issue 2, July 2019, Page 287-304  XML
Document Type: Original Article
DOI: 10.21608/mjeer.2019.62791
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Authors
Hanan Ghanem* ; Walid El-Shafai; El-Sayed El-Rabaie; Abd Naser Mohamed; Ahmed Rashed; Fathi Abd El-Samie; Mohammed Tabbour
Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering, Menouf 32951, Menoufia University, EGYPT
Abstract
This paper presents two efficient approaches for radiation effect identification using signal and image processing concepts. The first approach depends on k-means clustering performed on spectrometer counts versus wavelength. The other approach depends on the analysis of zebra chart image based on depth/edge model. Quality metrics of the received images are used for classification on of the cases with and without radiation. Simulation results reveal high efficiency of the two proposed approaches for radiation effect detection.
Keywords
Radiation detection; gamma radiation; K-mean clustering; Artificial Neural Networks; Image processing
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