Flashlight CNN Image Denoising

Flashlight CNN Image Denoising

This paper proposes a learning-based denoising method called FlashLight CNN (FLCNN) that implements a deep neural network for image denoising. The proposed approach is based on deep residual networks and inception networks and it is able to leverage many more parameters than residual networks alone...

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Veröffentlicht in:arXiv.org 2020-07
Hauptverfasser: Pham Huu Thanh Binh, Cruz, Cristóvão, Egiazarian, Karen
Format: Artikel
Sprache:eng
Schlagworte:
Artificial neural networks
Flashlights
Machine learning
Noise reduction
Random noise
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Zusammenfassung:This paper proposes a learning-based denoising method called FlashLight CNN (FLCNN) that implements a deep neural network for image denoising. The proposed approach is based on deep residual networks and inception networks and it is able to leverage many more parameters than residual networks alone for denoising grayscale images corrupted by additive white Gaussian noise (AWGN). FlashLight CNN demonstrates state of the art performance when compared quantitatively and visually with the current state of the art image denoising methods.
ISSN:2331-8422