scholarly journals Combined Full-Reference Image Quality Metrics for Objective Assessment of Multiply Distorted Images

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2256
Author(s):  
Krzysztof Okarma ◽  
Piotr Lech ◽  
Vladimir V. Lukin

In the recent years, many objective image quality assessment methods have been proposed by different researchers, leading to a significant increase in their correlation with subjective quality evaluations. Although many recently proposed image quality assessment methods, particularly full-reference metrics, are in some cases highly correlated with the perception of individual distortions, there is still a need for their verification and adjustment for the case when images are affected by multiple distortions. Since one of the possible approaches is the application of combined metrics, their analysis and optimization are discussed in this paper. Two approaches to metrics’ combination have been analyzed that are based on the weighted product and the proposed weighted sum with additional exponential weights. The validation of the proposed approach, carried out using four currently available image datasets, containing multiply distorted images together with the gathered subjective quality scores, indicates a meaningful increase of correlations of the optimized combined metrics with subjective opinions for all datasets.

2016 ◽  
Vol 16 (6) ◽  
pp. 316-325 ◽  
Author(s):  
Mariusz Oszust

Abstract The advances in the development of imaging devices resulted in the need of an automatic quality evaluation of displayed visual content in a way that is consistent with human visual perception. In this paper, an approach to full-reference image quality assessment (IQA) is proposed, in which several IQA measures, representing different approaches to modelling human visual perception, are efficiently combined in order to produce objective quality evaluation of examined images, which is highly correlated with evaluation provided by human subjects. In the paper, an optimisation problem of selection of several IQA measures for creating a regression-based IQA hybrid measure, or a multimeasure, is defined and solved using a genetic algorithm. Experimental evaluation on four largest IQA benchmarks reveals that the multimeasures obtained using the proposed approach outperform state-of-the-art full-reference IQA techniques, including other recently developed fusion approaches.


2019 ◽  
Vol 25 (5) ◽  
pp. 57-62 ◽  
Author(s):  
Krzysztof Okarma ◽  
Jaroslaw Fastowicz

Automatic visual quality assessment of the 3D printed surfaces is currently one of the most demanding challenges in additive manufacturing. Regardless of the applications of the computer vision for the 3D printing process monitoring purposes, a reliable surface quality evaluation during manufacturing may introduce brand new possibilities. The detection of some distortions and their automatic evaluation can be helpful when deciding to stop the process to save time, energy, and filament. In some cases, some further corrections can also be made for relatively small distortions. Since many general-purpose image quality assessment methods have been proposed in recent years, their applications for the quality evaluation in the additive manufacturing are investigated. As most of the metrics are full-reference and require the availability of the original perfect quality image, their direct application is not possible. Therefore, their adaptation is described in the paper together with experimental verification of classification results obtained using various metrics.


PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0199430 ◽  
Author(s):  
Chaofeng Li ◽  
Yifan Li ◽  
Yunhao Yuan ◽  
Xiaojun Wu ◽  
Qingbing Sang

Author(s):  
Yang Wen ◽  
Ying Li ◽  
Xiaohua Zhang ◽  
Wuzhen Shi ◽  
Lin Wang ◽  
...  

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