Analyst Performance Measures Volume Iii: Information Quality Tools for Persistent Surveillance Data Sets
نویسندگان
چکیده
Image quality assessment has a great importance in several image processingapplications. Recently, various objective image quality metrics have been proposed in order topredict the human visual perception. In this paper, novel image quality metrics, S-SSIM(saliency-based structural similarity index) and S-VIF (saliency-based visual informationfidelity), are proposed based on frequency-tuned salient region. Saliency maps are produced fromthe color and luminance features of the image. SSIM and VIF in pixel domain are modified by theweighting factors of the saliency maps. We validated our approach using 2 image databases astest bed: These databases contain subjective scores for each image. Our results showed that ourtechnique is more correlated with human subjective perception.
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