Joint Demosaicing and Denoising

4 papers with code • 8 benchmarks • 5 datasets

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Most implemented papers

Joint Demosaicing and Denoising With Self Guidance

laulampaul/sgnet CVPR 2020

In this paper, we propose a self-guidance network (SGNet), where the green channels are initially estimated and then works as a guidance to recover all missing values in the input image.

Beyond Joint Demosaicking and Denoising: An Image Processing Pipeline for a Pixel-bin Image Sensor

sharif-apu/BJDD_CVPR21 19 Apr 2021

In this paper, we tackle the challenges of joint demosaicing and denoising (JDD) on such an image sensor by introducing a novel learning-based method.

SAGAN: Adversarial Spatial-asymmetric Attention for Noisy Nona-Bayer Reconstruction

sharif-apu/sagan_bmvc21 The British Machine Vision Conference 2021

We combine our proposed module with adversarial learning to produce plausible images from Nona-Bayer CFA.

A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift

guoshi28/2stagealign CVPR 2022

Denoising and demosaicking are two essential steps to reconstruct a clean full-color image from the raw data.