Authors :
Gouri Sankar Nayak; B. Henry Amal; SK. S. Haneesha; M. Shivakumar; B.Lekhana; G.V. Chanukya Teja
Volume/Issue :
Volume 9 - 2024, Issue 4 - April
Google Scholar :
https://tinyurl.com/2n2umukp
Scribd :
https://tinyurl.com/3n8a92j7
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24APR932
Abstract :
The project introduces an innovative solution
to the persistent challenge of image blurring in the realm
of Computer Vision. Leveraging the synergies between
auto-encoder structures and Non-Linear Activation Free
Networks (NAFNET), the proposed methodology aims to
achieve superior image restoration results by effectively
addressing diverse types of blur. This approach offers a
holistic solution that combines the strengths of
traditional methods and state-of-the-art deep learning
techniques. Quantitative evaluation using metrics
demonstrates the efficacy of the proposed methodology
in achieving superior deblurring results compared to
existing techniques. By pushing the boundaries alongside
of image deblurring capabilities, the project contributes
to the advancement of the field and holds promise for
applications across various domains, including
photography, medical imaging, and surveillance.
Keywords :
Image Blurring, Auto-Encoder, Image Restoration, Quantitative.
The project introduces an innovative solution
to the persistent challenge of image blurring in the realm
of Computer Vision. Leveraging the synergies between
auto-encoder structures and Non-Linear Activation Free
Networks (NAFNET), the proposed methodology aims to
achieve superior image restoration results by effectively
addressing diverse types of blur. This approach offers a
holistic solution that combines the strengths of
traditional methods and state-of-the-art deep learning
techniques. Quantitative evaluation using metrics
demonstrates the efficacy of the proposed methodology
in achieving superior deblurring results compared to
existing techniques. By pushing the boundaries alongside
of image deblurring capabilities, the project contributes
to the advancement of the field and holds promise for
applications across various domains, including
photography, medical imaging, and surveillance.
Keywords :
Image Blurring, Auto-Encoder, Image Restoration, Quantitative.
