title: Multi-frame super-resolution with quality self-assessment for retinal fundus videos.
abstract: This paper proposes a novel super-resolution framework to reconstruct high-resolution fundus images from multiple low-resolution video frames in retinal fundus imaging. Natural eye movements during an examination are used as a cue for super-resolution in a robust maximum a-posteriori scheme. In order to compensate heterogeneous illumination on the fundus, we integrate retrospective illumination correction for photometric registration to the underlying imaging model. Our method utilizes quality self-assessment to provide objective quality scores for reconstructed images as well as to select regularization parameters automatically. In our evaluation on real data acquired from six human subjects with a low-cost video camera, the proposed method achieved considerable enhancements of low-resolution frames and improved noise and sharpness characteristics by 74%. In terms of image analysis, we demonstrate the importance of our method for the improvement of automatic blood vessel segmentation as an example application, where the sensitivity was increased by 13% using super-resolution reconstruction.
authors.forename: Thomas
authors.initials: T
authors.lastname: Köhler
authors.forename: Alexander
authors.initials: A
authors.lastname: Brost
authors.forename: Katja
authors.initials: K
authors.lastname: Mogalle
authors.forename: Qianyi
authors.initials: Q
authors.lastname: Zhang
authors.forename: Christiane
authors.initials: C
authors.lastname: Köhler
authors.forename: Georg
authors.initials: G
authors.lastname: Michelson
authors.forename: Joachim
authors.initials: J
authors.lastname: Hornegger
authors.forename: Ralf P
authors.initials: RP
authors.lastname: Tornow
mesh_terms: D000465:Algorithms; D005246:Feedback; D005654:Fundus Oculi; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000033:anatomy & histology*; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*