# Flashlight CNN Image Denoising

arXiv: https://arxiv.org/abs/2003.00762 · HTML: https://mlsanity.com/paper/2003.00762/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [Cross-boosting of WNNM Image Denoising method by Directional Wavelet Packets](https://mlsanity.com/paper/2206.04431/) (2022)

## Abstract (arXiv)

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.