Authors :
M. Gangappa; Eloori Karthik; Gaddampally Shreyas Reddy; Gudimetla Satya Manjunadha Reddy; Mohammad Shoaib
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
https://tinyurl.com/yuusmkpu
Scribd :
https://tinyurl.com/dtrx2y
DOI :
https://doi.org/10.5281/zenodo.10731661
Abstract :
Over time, images may undergo degradation
due to various factors, leading to loss of clarity and
visual appeal. The motivation behind this study is to aid
in the restoration of precious memories, as pictures serve
triggers for cherished recollections, and enhancing
image quality can improve clarity and visual comfort.
The significance of this research lies in its potential to
help individuals recover and preserve cherished
memories captured in damaged images. Restoring the
visual quality of images can evoke emotions and
facilitate stronger connections to the past. In recent past
AI has advanced significantly in these areas. However,
the potential for misinformation and deep fake
proliferation has raised concerns about the authenticity
and credibility of visual content. In response to this
challenge, we aimed at developing an automated system
to discern between AI- generated images and original
photographs with high accuracy. Additionally,
enhancing image quality has various practical benefits,
such as increased clarity, improved viability, and
reduced strain on the eyes when viewing the restored
images. Overall, this research demonstrates the
effectiveness of deep learning with GANs for image
restoration, highlighting its value in recovering
invaluable memories and enhancing visual content for
broader applications. The results of this study showcase
the potential of AI-driven image restoration techniques
to positively impact our personal lives and the way we
interact with visual data in the digital age.
Keywords :
Deep Learning, GAN, Machine Learning, Image In- Painting, Deep Fake.
Over time, images may undergo degradation
due to various factors, leading to loss of clarity and
visual appeal. The motivation behind this study is to aid
in the restoration of precious memories, as pictures serve
triggers for cherished recollections, and enhancing
image quality can improve clarity and visual comfort.
The significance of this research lies in its potential to
help individuals recover and preserve cherished
memories captured in damaged images. Restoring the
visual quality of images can evoke emotions and
facilitate stronger connections to the past. In recent past
AI has advanced significantly in these areas. However,
the potential for misinformation and deep fake
proliferation has raised concerns about the authenticity
and credibility of visual content. In response to this
challenge, we aimed at developing an automated system
to discern between AI- generated images and original
photographs with high accuracy. Additionally,
enhancing image quality has various practical benefits,
such as increased clarity, improved viability, and
reduced strain on the eyes when viewing the restored
images. Overall, this research demonstrates the
effectiveness of deep learning with GANs for image
restoration, highlighting its value in recovering
invaluable memories and enhancing visual content for
broader applications. The results of this study showcase
the potential of AI-driven image restoration techniques
to positively impact our personal lives and the way we
interact with visual data in the digital age.
Keywords :
Deep Learning, GAN, Machine Learning, Image In- Painting, Deep Fake.
