Reference-free Image Quality Assessment Algorithm Based on Visual Characteristics
Concerning the problems in the traditional reference-free image quality assessment algorithms,such as only single features are used,subjective assessment results are needed in training,and poor performance for contrast distortion images,an improved algorithm is pro-posed based on color and texture features and visual characteristics.Firstly,a pseudo-reference image is constructed for an image to be evalu-ated,and both are divided into primary and secondary regions of interest according to the visual characteristics.Secondly,the regions are fur-ther divided into smaller blocks,and then different color and texture features are extracted for each block and multivariate Gaussian models are established.Finally,the model parameter distances between the main regions of interest and the secondary regions of interest are calculat-ed as a quality score to evaluate the quality of image.Using the public datasets SPAQ and CSIQ and comparing with the traditional algorithms QAC,NIQE,IL-NIQE,etc.by calculating the values of evaluation indicators of linear Pearson coefficient,Spearman rank correlation coeffi-cient,and root mean square error,the results show that the proposed algorithm outperforms the traditional ones.
reference-free image quality assessmentvisual characteristicspseudo-reference imagesMVG modeltexture featurescol-or features
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