18 April 2006 Advanced image quality assessment approach using multiple quality measures with the artificial neural network data processing support
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Proceedings Volume 6180, Photonics, Devices, and Systems III; 61801Z (2006); doi: 10.1117/12.675848
Event: Photonics, Devices, and Systems III, 2005, Prague, Czech Republic
Abstract
This paper deals with the subjective and objective image quality evaluation. The demand of an accurate image and video objective quality assessment tool is extremely important in modern multimedia systems. Possible enhancement of the performance in existent image quality assessment approaches using multiple quality measures with the support of the artificial neural network data processing is proposed. The analysis results of the known quality measures and their suitability for the particular image or video quality assessment problem are presented. The most suitable measures are used to implement the novel image quality assessment tool using artificial neural network data processing. Optimization of the proposed model has been done in order to achieve as highest generalization feature of the model as possible. Performance of the implemented model for the image quality assessment has been evaluated using the database of distorted images and subjective image quality assessment results with respect to the Mean Opinion Score (MOS) obtained by the group of observers. It is shown that the proposed image quality assessment model can achieve high correlation with the subjective image quality ratings.
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Karel Fliegel, "Advanced image quality assessment approach using multiple quality measures with the artificial neural network data processing support", Proc. SPIE 6180, Photonics, Devices, and Systems III, 61801Z (18 April 2006); doi: 10.1117/12.675848; https://doi.org/10.1117/12.675848
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KEYWORDS
Image quality

Molybdenum

Image compression

Artificial neural networks

Image processing

Quality measurement

Data processing

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