Abstract
Image quality assessment (IQA) is a critical issue in image processing applications, but traditional criteria based on the differences between reference and distorted images do not correlate well with perceived quality. MSSIM and VIF criteria proposed recently are regarded as excellent models in comparison with others, but they only consider local features and ignore some global concepts. In this paper, we propose an improved method that adds global saliency features to the criteria of MSSIM and VIF. For the sake of reducing the computational complexity, we propose a simpler and faster method to extract the saliency map. Experimental results for a set of intuitive examples as well as validation on a database of 779 images with different distortion types demonstrate that the improved IQA criteria can get a better performance than their original forms.
This work is supported by the National Nature Science Foundation of China (60571052) and Shanghai Leading Academic Discipline Project (B112).
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Ma, Q., Zhang, L. (2008). Saliency-Based Image Quality Assessment Criterion. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_139
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DOI: https://doi.org/10.1007/978-3-540-87442-3_139
Publisher Name: Springer, Berlin, Heidelberg
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