Subjective image quality prediction based on neural network.
Sertan Kaya, Mariofanna G. Milanova, John R. Talburt, Brian Huong-Peng Tsou, Marina Altynovac · ICIQ · 2011
This paper investigates the applicability of the Neural Network approach for image quality assessment. The aim is to predict the subjective quality score, namely the difference mean opinion score (DMOS) obtained from human observers, by incorporating a neural network algorithmic approach utilizing extracted statistical features from test and original images. To ease this approach, a MATLAB user interface is developed and presented here. To validate the proposed approach, an image database is selected consisting of various distortion types as test bed in which a DMOS value is provided for each distorted image. Experimental results show that the obtained output of Neural Network correlates well with DMOS values and Neural Network can mimic human observers.