[IPOL announce] new article: An Analysis and Implementation of the HDR+ Burst Denoising Method

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2021/336/

Antoine Monod, Julie Delon, and Thomas Veit,
An Analysis and Implementation of the HDR+ Burst Denoising Method,
Image Processing On Line, 11 (2021), pp. 142–169.
https://doi.org/10.5201/ipol.2021.336

Abstract
HDR+ is an image processing pipeline presented by Google in 2016. At its 
core lies a denoising algorithm that uses a burst of raw images to 
produce a single higher quality image. Since it is designed as a 
versatile solution for smartphone cameras, it does not necessarily aim 
for the maximization of standard denoising metrics, but rather for the 
production of natural, visually pleasing images. In this article, we 
specifically discuss and analyze the HDR+ burst denoising algorithm 
architecture and the impact of its various parameters. With this 
publication, we provide an open source Python implementation of the 
algorithm, along with an interactive demo.