Deep Image Prior for Super Resolution of Noisy Image
نویسندگان
چکیده
Single image super-resolution task aims to reconstruct a high-resolution from low-resolution image. Recently, it has been shown that by using deep prior (DIP), single neural network is sufficient capture low-level statistics only without data-driven training such can be used for various restoration problems. However, tasks are difficult perform with DIP when the target noisy. The super-resolved becomes noisy because reconstruction loss of does not consider noise in Furthermore, contains noise, optimization process unstable and sensitive noise. In this paper, we propose noise-robust stable framework based on DIP. To end, noise-estimation method generative adversarial (GAN) self-supervision (SSL). We show generator learn distribution proposed framework. Moreover, argue stabilized incorporated. experiments quantitatively qualitatively outperforms existing methods images.
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ژورنال
عنوان ژورنال: Electronics
سال: 2021
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics10162014