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 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.
- Tampere University Finland
FOS: Computer and information sciences, Computer Science - Machine Learning, Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, Machine Learning (cs.LG)
FOS: Computer and information sciences, Computer Science - Machine Learning, Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, Machine Learning (cs.LG)
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