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On Finding Gray Pixels

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Details

Original languageEnglish
Title of host publication2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PublisherIEEE
Pages8054-8062
Number of pages9
ISBN (Electronic)978-1-7281-3293-8
ISBN (Print)978-1-7281-3294-5
DOIs
Publication statusPublished - Jun 2019
Publication typeA4 Article in a conference publication
EventIEEE/CVF Conference on Computer Vision and Pattern Recognition -
Duration: 1 Jan 2000 → …

Publication series

NameIEEE/CVF Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919
ISSN (Electronic)2575-7075

Conference

ConferenceIEEE/CVF Conference on Computer Vision and Pattern Recognition
Abbreviated titleCVPR
Period1/01/00 → …

Abstract

We propose a novel grayness index for finding gray pixels and demonstrate its effectiveness and efficiency in illumination estimation. The grayness index, GI in short, is derived using the Dichromatic Reflection Model and is learning-free. GI allows to estimate one or multiple illumination sources in color-biased images. On standard single-illumination and multiple-illumination estimation benchmarks, GI outperforms state-of-the-art statistical methods and many recent deep methods. GI is simple and fast, written in a few dozen lines of code, processing a 1080p image in ~0.4 seconds with a non-optimized Matlab code.

Keywords

  • Computational Photography, Low-level Vision, Statistical Learning

Publication forum classification

Field of science, Statistics Finland