Analyzing Image Denoising Using Generative Adversarial Network

Authors

  • Dr.S. Saranya
  • Pavan Kumar Vellaturi
  • Venkateshwar Rao Velichala
  • Chaitanya Kumar Vemula

DOI:

https://doi.org/10.47750/pnr.2022.13.S03.049

Keywords:

GAN, CNN, Image Restoration, Convolution, Blurred Images, Noise.

Abstract

Motion images they have great use in television and film making and virtual reality technology. This paper gives the solution of reconstruction the dynamic blur images.it converts from blur images to actual images by the mapping, it can be happened by using an image reconstruction algorithm using the GAN convolution model. The model runs on the input sets and the output will be an actual image that came from the blur images. The restoration effect will be good and quality is high in terms of stability, phase manipulation, conversion efficiency, noise performance.

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Published

2022-09-22

Issue

Section

Articles

How to Cite

Analyzing Image Denoising Using Generative Adversarial Network. (2022). Journal of Pharmaceutical Negative Results, 307-310. https://doi.org/10.47750/pnr.2022.13.S03.049