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27 January 2014 Restoration of retinal images with space-variant blur
Andres G. Marrugo, Maria S. Millan, Michal Sorel, Filip Sroubek
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Journal of Biomedical Optics, Vol. 19, Issue 1, 016023 (January 2014). https://doi.org/10.1117/1.JBO.19.1.016023
Abstract
Retinal images are essential clinical resources for the diagnosis of retinopathy and many other ocular diseases. Because of improper acquisition conditions or inherent optical aberrations in the eye, the images are often degraded with blur. In many common cases, the blur varies across the field of view. Most image deblurring algorithms assume a space-invariant blur, which fails in the presence of space-variant (SV) blur. In this work, we propose an innovative strategy for the restoration of retinal images in which we consider the blur to be both unknown and SV. We model the blur by a linear operation interpreted as a convolution with a point-spread function (PSF) that changes with the position in the image. To achieve an artifact-free restoration, we propose a framework for a robust estimation of the SV PSF based on an eye-domain knowledge strategy. The restoration method was tested on artificially and naturally degraded retinal images. The results show an important enhancement, significant enough to leverage the images’ clinical use.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
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Andres G. Marrugo, Maria S. Millan, Michal Sorel, and Filip Sroubek "Restoration of retinal images with space-variant blur," Journal of Biomedical Optics 19(1), 016023 (27 January 2014). https://doi.org/10.1117/1.JBO.19.1.016023
Published: 27 January 2014
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Cited by 8 scholarly publications.
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KEYWORDS
Point spread functions
Eye
Convolution
Cameras
Blood vessels
Deconvolution
Optical aberrations
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