التفاصيل البيبلوغرافية
| العنوان: |
Doing More With Moiré Pattern Detection in Digital Photos. |
| المؤلفون: |
Yang, Cong1 (AUTHOR) yangcong955@126.com, Yang, Zhenyu2 (AUTHOR), Ke, Yan3 (AUTHOR), Chen, Tao1 (AUTHOR), Grzegorzek, Marcin4 (AUTHOR), See, John5 (AUTHOR) |
| المصدر: |
IEEE Transactions on Image Processing. 2023, Vol. 32, p694-708. 15p. |
| مصطلحات موضوعية: |
*TASK analysis, IMAGE reconstruction, DIGITAL photography, PHOTOGRAPHS, MIXTURES |
| مستخلص: |
Detecting moiré patterns in digital photographs is meaningful as it provides priors towards image quality evaluation and demoiréing tasks. In this paper, we present a simple yet efficient framework to extract moiré edge maps from images with moiré patterns. The framework includes a strategy for training triplet (natural image, moiré layer, and their synthetic mixture) generation, and a Moiré Pattern Detection Neural Network (MoireDet) for moiré edge map estimation. This strategy ensures consistent pixel-level alignments during training, accommodating characteristics of a diverse set of camera-captured screen images and real-world moiré patterns from natural images. The design of three encoders in MoireDet exploits both high-level contextual and low-level structural features of various moiré patterns. Through comprehensive experiments, we demonstrate the advantages of MoireDet: better identification precision of moiré images on two datasets, and a marked improvement over state-of-the-art demoiréing methods. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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