Survey on CNN based super resolution methods

  • Rafaa Amen Kazem Mustansiriyah University, College of Science, Computer Science Department., Baghdad, Iraq
  • Jamila H. Suad Mustansiriyah University, College of Science, Computer Science Department, Baghdad, Iraq
  • Huda Abdulaali Abdulbaqi Mustansiriyah University, College of Science, Computer Science Department, Baghdad, Iraq
Keywords: CNN, VSDR, FSRCNN, DRCN

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.

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Published
2021-09-27
How to Cite
Kazem, R. A., Suad, J. H., & Abdulbaqi, H. A. (2021). Survey on CNN based super resolution methods. Journal La Multiapp, 2(4), 27-33. https://doi.org/10.37899/journallamultiapp.v2i4.444