Institute of Information Theory and Automation

Publication details

Towards super-resolution in the presence of spatially varying blur

Monography Chapter

Šorel Michal, Šroubek Filip, Flusser Jan


serial: Super-resolution imaging, p. 1-38 , Eds: Milanfar Peyman

research: CEZ:AV0Z10750506

project(s): 1M0572, GA MŠk, GA102/08/1593, GA ČR

keywords: image processing, image restoration, super-resolution

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abstract (eng):

The effective resolution of an imaging system is limited not only by the physical resolution of an image sensor but also by blur. If the blur is present, super-resolution makes little sense without removing the blur. Some super-resolution methods considering space-invariant blur are described in other chapters of this book. The presence of a /emph{spatially varying blur} makes the problem much more challenging and for the present, there are almost no algorithms designed specifically for this case. We argue that the critical part of such algorithms is precise estimation of the varying blur, which depends to large extent on a specific application and type of blur. In this chapter, we discuss possible sources of spatially varying blur, such as defocus, camera motion or object motion. In each case we review known approaches to blur estimation, illustrate their performance on experiments with real data and indicate problems that must be solved to be applicable in super-resolution algorithms.

RIV: JD

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Last modification: 21.12.2012
Institute of Information Theory and Automation