University of Bahrain
Scientific Journals

Enhancing Visual Realism with Convolutional Neural Networks

Show simple item record K.S, Swarnalatha 2023-07-19T06:00:50Z 2023-07-19T06:00:50Z 2023-07-19
dc.identifier.issn 2210-142X
dc.description.abstract This research addresses the challenge of blurry and low-resolution images, which often lack the necessary information for effective user perception. Blurriness in images can occur due to various factors such as camera movement, improper focus, aperture settings, and external influences, resulting in degraded or deteriorated photographs. Additionally, the presence of haze, whether uniform or non-uniform, can further contribute to image distortion and poor quality. To tackle these issues, a deep learning approach utilizing convolutional neural networks (CNNs) is proposed. This approach simultaneously addresses image de-blurring and super resolution, providing a comprehensive solution. By employing super resolution techniques, it becomes possible to enhance the quality of images significantly, generating high-resolution outputs from low resolution inputs. The use of neural networks, particularly CNNs, demonstrates experimental superiority over existing deep learning algorithms, leveraging the benefits of super resolution. The suggested model exhibits scientific evidence of the effectiveness and efficiency of the proposed system. It demonstrates that the quality and quantity of the system's performance are achieved. Regardless of the level of blur in the input images, the proposed model can achieve high-quality resolution, surpassing the limitations of current approaches. By employing a profound learning strategy through CNNs, both known and unknown levels of blur can be effectively addressed, resulting in superior image restoration and enhancement. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject CNN en_US
dc.subject Blur en_US
dc.subject High resolution en_US
dc.subject images en_US
dc.subject deblurring en_US
dc.title Enhancing Visual Realism with Convolutional Neural Networks en_US
dc.volume 14 en_US
dc.issue 1 en_US
dc.pagestart 1 en_US
dc.pageend xx en_US
dc.contributor.authorcountry India en_US
dc.contributor.authoraffiliation Nitte Meenakshi Institute of Technology en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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