Restoration of retinal images with space-variant blur
Universidad Tecnológica de Bolívar
Metadata Show full item record
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.
This research has been partly funded by the Spanish Ministerio de Ciencia e Innovación y Fondos FEDER (project DPI2009-08879) and projects TEC2010-09834-E and TEC2010-20307. Financial support was also provided by the Grant Agency of the Czech Republic under project 13-29225S. Authors are grateful to Juan Luís Fuentes from the Miguel Servet University Hospital (Zaragoza, Spain) for providing images. The first author also thanks the Spanish Ministerio de Educación for an FPU doctoral scholarship.
Compatible para recolección con: