Evaluation of super-resolution methods in the context of colonic polyp classification
Michael R. Hafner, Michael Liedlgruber, Andreas Uhl, Georg Wimmer · 2014
In this work we investigate whether it is possible to improve the results of an automated classification of colonic polyps by using super-resolution algorithms on endoscopic video sequences. For this purpose we apply different super-resolution methods to endoscopic sequences and use a set of feature extraction methods for the classification of the SR reconstruction results. We then compare the results obtained from these experiments against the classification results based on original low-resolution frames and against classification rates based on upscaled versions of low-resolution frames. We show that, at least for the set of super-resolution methods and feature extraction methods evaluated, applying superresolution methods to the low-resolution frames has no significant impact on the resulting overall classification results.