Abstract
Developing reduced reference image quality assessment (RR-IQA) plays a vital role in dealing with the prediction of the visual quality of distorted images. However, most of existing methods fail to take color information into consideration, although the color distortion is significant for the increasing color images. To solve the aforementioned problem, this paper proposed a novel IQA method which focuses on the color distortion. In particular, we extract color features based on the model of color fractal structure. Then the color and structure features are mapped into visual quality using the support vector regression. Experimental results on the LIVE II database demonstrate that the proposed method has a good consistency with the human perception especially on images with color distortion.
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He, L., Wang, D., Li, X., Tao, D., Gao, X., Gao, F. (2012). Color Fractal Structure Model for Reduced-Reference Colorful Image Quality Assessment. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_49
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DOI: https://doi.org/10.1007/978-3-642-34481-7_49
Publisher Name: Springer, Berlin, Heidelberg
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