An Efficient Enhancement Framework for Videoscope Images in Electric Supply Surveillance Applications

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL An Efficient Enhancement Framework for Videoscope Images in Electric Supply Surveillance Applications 13 Pages Posted: 21 May 2022 See all articles by Noha A. El-HagNoha A. El-HagMenoufia UniversitySahar AboshoshaMinia UniversityWalid El-ShafaiMenoufia UniversityEl-Sayed M. El-RabaieMenoufia UniversityAshraf A. M. Khalafaffiliation not provided to SSRNFathi E. Abd El-SamieMenoufia University Abstract This paper presented an efficient framework for videoscope image optimization. This framework is based on super resolution Convolutional Neural Network (CNN) model and fuzzy technique. Firstly, the videoscope images are improved by employing wavelet multi-scale CNN. The CNN is trained with respect to analysis of the wavelet and it trained multiple times to approximate the wavelet multi-scale representations in separate way. The wavelet decomposition is applied to videoscope images for multi- scale representation. And then, the restoration of the High Resolution (HR) images can be achieved. Finally, the fuzzy technique is implemented to highlight the important features of the images. Keywords: Fuzzy technique, Super resolution, HR images, CNN, Vedioscope images Suggested Citation: Suggested Citation El-Hag, Noha A. and Aboshosha, Sahar and El-Shafai, Walid and El-Rabaie, El-Sayed M. and Khalaf, Ashraf A. M. and El-Samie, Fathi E. Abd, An Efficient Enhancement Framework for Videoscope Images in Electric Supply Surveillance Applications. Available at SSRN: https://ssrn.com/abstract=4116225 Noha A. El-Hag (Contact Author) Menoufia University ( email ) Gamal Abd El-Nasir,Shebeen El-KomEgypt Sahar Aboshosha Minia University ( email ) Egypt Walid El-Shafai Menoufia University ( email ) Gamal Abd El-Nasir,Shebeen El-KomEgypt El-Sayed M. El-Rabaie Menoufia University ( email ) Gamal Abd El-Nasir,Shebeen El-KomEgypt Ashraf A. M. Khalaf affiliation not provided to SSRN ( email ) No Address Available Fathi E. Abd El-Samie Menoufia University ( email ) Gamal Abd El-Nasir,Shebeen El-KomEgypt Download This Paper Open PDF in Browser Do you want regular updates from SSRN on Twitter? Follow SSRN Paper statistics Downloads 0 Abstract Views 9 PlumX Metrics Related eJournals Information Systems eJournal Follow Information Systems eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 221 PAPERS 4,293 Other Information Systems & eBusiness eJournal Follow Other Information Systems & eBusiness eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 1 PAPERS 6,163 Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages SSRN Quick Links SSRN Solutions Research Paper Series Conference Papers Partners in Publishing Jobs & Announcements Newsletter Sign Up SSRN Rankings Top Papers Top Authors Top Organizations About SSRN SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy We use cookies to help provide and enhance our service and tailor content. To learn more, visit Cookie Settings. This page was processed by aws-apollo4 in 0.337 seconds