Institute of Information Theory and Automation

Publication details

Advances in image restoration: from theory to practice


Šroubek Filip

serial: Digital Photography XI

action: Digital Photography and Mobile Imaging XI, (San Francisco, US, 09.02.2015-10.02.2015)

project(s): M100751201, GA AV ČR, 621439,

keywords: deconvolution, superresolution, review

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abstract (eng):

We rely on images with ever growing emphasis. Our perception of the world is however limited by imperfect measuring conditions and devices used to acquire images. By image restoration, we understand mathematical procedures removing degradation from images. Two prominent topics of image restoration that has evolved considerably in the last 10 years are blind deconvolution and superresolution. Deconvolution by itself is an ill-posed inverse problem and one of the fundamental topics of image processing. The blind case, when the blur kernel is also unknown, is even more challenging and requires special optimization approaches to converge to the correct solution. Superresolution extends blind deconvolution by recovering lost spatial resolution of images. In this talk we will cover the recent advances in both topics that pave the way from theory to practice. Various real acquisition scenarios will be discussed together with proposed solutions for both blind deconvolution and superresolution and efficient numerical optimization methods, which allow fast implementation. Examples with real data will illustrate performance of the proposed solutions.


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Last modification: 21.12.2012
Institute of Information Theory and Automation