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All Journal Journal La Multiapp
Huda Abdulaali Abdulbaqi
Mustansiriyah University, College of Science, Computer Science Department, Baghdad, Iraq
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Engineering

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Survey on CNN based super resolution methods Rafaa Amen Kazem; Jamila H. Suad; Huda Abdulaali Abdulbaqi
Journal La Multiapp Vol. 2 No. 4 (2021): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v2i4.444

Abstract

Super Resolution is a field of image analysis that focuses on boosting the resolution of photographs and movies without compromising detail or visual appeal, instead enhancing both. Multiple (many input images and one output image) or single (one input and one output) stages are used to convert low-resolution photos to high-resolution photos. The study examines super-resolution methods based on a convolutional neural network (CNN) for super-resolution mapping at the sub-pixel level, as well as its primary characteristics and limitations for noisy or medical images.
Co-Authors Jamila H. Suad Rafaa Amen Kazem