An Analysis and Implementation of the HDR+ Burst Denoising Method
Antoine Monod, Julie Delon, Thomas Veit
⚠ This is a preprint. It may change before it is accepted for publication.

Abstract

HDR+ is an image processing pipeline presented by Google in 2016. At its core lies a denoising algorihtm 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 maximisation of standard denoising metrics, 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.

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