[IPOL announce] new article: A Study of Two CNN Demosaicking Algorithms

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2019/274/

Thibaud Ehret, and Gabriele Facciolo,
A Study of Two CNN Demosaicking Algorithms,
Image Processing On Line, 9 (2019), pp. 220–230.
https://doi.org/10.5201/ipol.2019.274

Abstract
Most cameras capture the information of only one color for a given 
pixel. This results in a mosaicked image that must be interpolated to 
get three colors at each pixel. The step going from a mosaicked image to 
a regular RGB image is called demosaicking. This paper studies two 
recent demosaicking methods based on convolutional neural networks that 
achieve artifact-free state-of-the-art results: Deep joint demosaicking 
and denoising by Gharbi et al. and Color image demosaicking via deep 
residual learning by Tan et al. We show that these methods beat by 
almost two decibels the best human-crafted methods, while being faster 
by one order of magnitude. This, arguably, seals the destiny of 
human-crafted methods on this subject.