Institute of Information Theory and Automation

Publication details

PSF accuracy measure for evaluation of blur estimation algorithms

Conference Paper (international conference)

Kotera Jan, Zitová Barbara, Šroubek Filip

serial: Proceedings of the 2015 IEEE International Conference on Image Processing, ICIP 2015, p. 2080-2084

action: IEEE International Conference on Image Processing 2015, ICIP 2015, (Québec City, CA, 27.09.2015-30.09.2015)

project(s): GA13-29225S, GA ČR, 938213/2013, GA UK, 7H14004, GA MŠk

keywords: image deconvolution, blur estimation, PSF error, PSF comparison, image restoration

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abstract (eng):

Given the large amount of blur estimation and blind deconvolution methods just in the last decade, there is an increasing need to compare the performance of a particular method with others. Unlike in other fields in image processing, there are very few well-established benchmark databases of test data and, more importantly, no standard way of performance evaluation. In this paper, we focus on the latter. We propose a new error measure for the blur kernel – a method for comparison of the blur estimate with the ground truth – which correctly reflects how inaccuracies in the blur estimation affect the subsequent image restoration, without the necessity to perform the actual deconvolution.


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Institute of Information Theory and Automation