title: Image deconvolution by means of frequency blur invariant concept.
abstract: Different blur invariant descriptors have been proposed so far, which are either in the spatial domain or based on the properties available in the moment domain. In this paper, a frequency framework is proposed to develop blur invariant features that are used to deconvolve a degraded image caused by a Gaussian blur. These descriptors are obtained by establishing an equivalent relationship between the normalized Fourier transforms of the blurred and original images, both normalized by their respective fixed frequencies set to one. Advantage of using the proposed invariant descriptors is that it is possible to estimate both the point spread function (PSF) and the original image. The performance of frequency invariants will be demonstrated through experiments. An image deconvolution is done as an additional application to verify the proposed blur invariant features.
authors.affiliation: Integrated Lightwave Research Group, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Lembah Pantai, Kuala Lumpur, Malaysia.
authors.forename: Barmak
authors.identifier: 0000-0003-1519-9596
authors.initials: B
authors.lastname: Honarvar Shakibaei
authors.affiliation: Integrated Lightwave Research Group, Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Lembah Pantai, Kuala Lumpur, Malaysia.
authors.forename: Peyman
authors.identifier: 0000-0003-0951-3008
authors.initials: P
authors.lastname: Jahanshahi
mesh_terms: D000465:Algorithms; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical