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Depth-of-field effect in subjective and objective evaluation of image quality

Zhang, Tingting, Nefs, Harold, Liu, Hantao ORCID:, Xia, Ling, Liu, Xiaofeng ORCID: and Wu, Xiaoli 2018. Depth-of-field effect in subjective and objective evaluation of image quality. Presented at: ACM RACS 2018 : 2018 ACM Research in Adaptive and Convergent Systems, Honololu, HI, USA, 9-12 October 2018. RACS '18: Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems. New York: ACM, pp. 308-312. 10.1145/3264746.3264757

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Depth of field, as an important image feature, is always ignored when assessing the quality of photographs. The current study compared the subjective image quality evaluation with three NR image quality algorithms: BIQI, BRISQUE, and NIQE on the performance of scoring photographs with different levels of depth of field. The results showed that a large depth of field led to higher image quality in BRISQUE and depth of field did not influence the performance of the other two objective metrics and human perception. We also concluded that objective metrics such as BRISQUE, NIQE, BIQI underestimated the image quality of photographs compared with human perception.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: ACM
ISBN: 978-1-4503-5885-9
Last Modified: 25 Oct 2022 13:06

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