Deep Neural Networks for Image Denoising
Huu Thanh Binh, Pham (2020)
2020
Degree Programme in Information Technology, MSc (Tech)
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2020-04-27
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202003302958
https://urn.fi/URN:NBN:fi:tuni-202003302958
Tiivistelmä
This master thesis introduces non-local, learning based denoising methods and proposes a new method called FlashLight CNN for denoising gray-scale images corrupted by additive white Gaussian noise (AWGN). The proposed method is designed based on the combination of deep convolutional and inception networks that improves the learning capacity of the deep neural networks by addressing typical training deep neural networks problems.
The proposed method demonstrates state-of-the-art performance both based on quantitative and visual evaluations.
The proposed method demonstrates state-of-the-art performance both based on quantitative and visual evaluations.