Synthetic Defocus Generation using Deep Learning

Mendjoge, Rutvik (2021) Synthetic Defocus Generation using Deep Learning. Masters thesis, Dublin, National College of Ireland.

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Abstract

Synthetic Defocus (Bokeh) is a common photographic technique for displaying in-focus objects. It focuses on the main subject of a picture while defocusing on all other objects. DSLR cameras are mostly used for this purpose. To capture bokeh, a smaller aperture is required. Many cellphones can now shoot this image as a result of technical advancements. The method used in this study is to achieve synthetic defocus on existing images. Using deep learning techniques, the concept can be accomplished. To have a comprehensive analysis of the image, it is necessary to examine all of the factors, therefore the idea of Deep Neural Networks is emphasized. DeepLab, Mask-RCNN, and Xception are three Deep Learning Algorithms that were used on the EBB Data set. Three evaluation metrics, such as PSNR, SSIM, and MSE, were used to evaluate these algorithms. DeepLab excelled in edge detection with smooth edges and excellent PSNR values when compared with the state of the art algorithms.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software T Technology > TR Photography
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Clara Chan
Date Deposited:	09 Dec 2021 12:14
Last Modified:	09 Dec 2021 12:14
URI:	https://norma.ncirl.ie/id/eprint/5191

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