Abstract
Tone-mapped images are the low dynamic range (LDR) images converted from high dynamic range (HDR) images. Recently, the objective quality assessment of tone-mapped images is becoming a challenging problem. However, there is no mature algorithm to deal with this issue until the tone-mapped image quality index (TMQI) was proposed recently, which is tone-mapped image quality index (TMQI). Unfortunately, the pooling method of the structural fidelity map in TMQI is the simple “mean”, which makes the result unsatisfying. On the other hand, recent studies have found that different locations of an image may have different contributions to the quality perception of the human visual system. The significance of a local image region can be well characterized by a visual saliency (VS) model. Inspired by this insight, in this paper, we propose a VS-based pooling strategy for the objective quality assessment of tone-mapped images. The experimental results clearly demonstrate the efficacy of our proposed method.
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Liu, X., Zhang, L., Li, H., Lu, J. (2014). Integrating Visual Saliency Information into Objective Quality Assessment of Tone-Mapped Images. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_41
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DOI: https://doi.org/10.1007/978-3-319-09333-8_41
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