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Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools
Author(s) -
BABALOUKAS GEORGIOS,
TENTOLOURIS NICHOLAS,
LIATIS STAVROS,
SKLAVOUNOU ALEXANDRA,
PERREA DESPOINA
Publication year - 2011
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.2011.03546.x
Subject(s) - vignetting , computer science , artificial intelligence , software , computer vision , optics , lens (geology) , physics , programming language
Summary Correction of vignetting on images obtained by a digital camera mounted on a microscope is essential before applying image analysis. The aim of this study is to evaluate three methods for retrospective correction of vignetting on medical microscopy images and compare them with a prospective correction method. One digital image from four different tissues was used and a vignetting effect was applied on each of these images. The resulted vignetted image was replicated four times and in each replica a different method for vignetting correction was applied with fiji and gimp software tools. The highest peak signal‐to‐noise ratio from the comparison of each method to the original image was obtained from the prospective method in all tissues. The morphological filtering method provided the highest peak signal‐to‐noise ratio value amongst the retrospective methods. The prospective method is suggested as the method of choice for correction of vignetting and if it is not applicable, then the morphological filtering may be suggested as the retrospective alternative method.