Abstract
Depth-Image-Based-Rendering (DIBR) is a fundamental technique used in free Viewpoint Videos (FVVs) to create new frames from existing adjacent frames, which can decrease the cost of camera set up. However, it is unavoidable to introduce geometric distortions in the synthesized images because of the warping and rendering operations in DIBR. Only a few Image Quality Assessment (IQA) methods have been proposed for such images and they are all Full-Reference (FR) methods. Nevertheless, reference DIBR-synthesized image is not accessible in real application scenarios, so No-Reference (NR) methods are more valuable than FR methods. In this paper, we propose an effective and efficient NR method based on Joint Photographic Experts Group (JPEG) image compression technology. The proposed method utilizes the difference of the amount of detail information between undistorted areas and geometry distortions areas, which can be achieved by comparing original images and JPEG images. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.
This work was supported in part by National Natural Science Foundation of China under Grants 61533002.
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Li, S., Qiao, J., Liu, M., Wu, L. (2018). Compression-Based Quality Predictor of 3D-Synthesized Views. In: Zhai, G., Zhou, J., Yang, X. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2017. Communications in Computer and Information Science, vol 815. Springer, Singapore. https://doi.org/10.1007/978-981-10-8108-8_29
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DOI: https://doi.org/10.1007/978-981-10-8108-8_29
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