| Citation: | WU Zhishan, ZHANG Shuai, NIU Yuzhenet al. Retargeted image quality assessment based on multi-scale distortion-aware feature[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(12): 2487-2494. doi: 10.13700/j.bh.1001-5965.2019.0368(in Chinese)
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The subjective visual experience of viewing images using a variety of display devices is usually affected by image retargeting operation. To improve the consistency between subjective perception and objective assessment for the retargeted images, we present an objective retargeted image quality assessment (RIQA) method based on multi-scale distortion-aware (MSDA) features. Because semantic distortion and detail distortion appear on different scales of the image, we propose to extract distortion-aware features from multiple scales of the image. Specifically, we present an accurate measurement for the aspect ratio similarity (ARS) between the original and retargeted images. Furthermore, we use a fused visual attention map to simulate the subjective attention of the human visual system to the image. The experimental results on the two benchmark databases show that the Kendall rank correlation coefficient (KRCC), Pearson linear correlation coefficient (PLCC), and Spearman rank-order correlation coefficient (SRCC) indicators of the proposed MSDA method are 4.1%, 1.8%, and 4.5% higher than the optimal method in the comparative methods, respectively.
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