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Video and Image Quality Estimation for Blur and Defocus Removement

Student: Dariia Kuvshinova

Supervisor: Ilya Makarov

Faculty: Faculty of Computer Science

Educational Programme: Data Science (Master)

Year of Graduation: 2020

With wide spread of hand-held cameras and growing demand in image and video applications, the problem of content quality estimation and quality enhancement arises. In this work we will focus on blur detection and removal since it is a common quality degradation factor, which can be produced by camera being out of focus, camera shake or object motions. Here we will provide an extensive literature review on blur removal methods for single-images and videos as well as mention necessary quality assessment metrics. Blur removal methods would be describes, classified and compared. Key words: motion blur, out-of-focus blur, single-image blur removal, video blur removal, image deblur, video deblur

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