NDLI: Natural image illuminant estimation via deep non-negative matrix factorisation

Content Provider	IET Digital Library
Author	Liu, Xiaopeng Zhong, Guoqiang Dong, Junyu
Abstract	The influence of environmental light sources affects the colour cast in natural images. In computer vision, biased colours have a significant influence on object recognition and classification. Illuminant estimation aims to eliminate these effects and obtain the image in canonical white light. In this study, the authors propose a deep non-negative matrix factorisation (DeepNMF) method to estimate the illuminant of colour-biased images. DeepNMF deeply factorises the input matrix into multiple layers, separating the image into patches and reshaping each channel of the patch as an [R,G,B] matrix. Based on the diagonal model, they assume that the final layer is the estimated illuminant of each patch. Mean pooling is then used to estimate the illuminant of the overall image. The angular error is used as a metric to test the authors’ method on three commonly used colour constancy datasets. The results show that the proposed method is comparable to state-of-the-art methods, although it is simpler to implement. As the proposed method uses a single image as input, it does not require a learning process.
Starting Page	121
Ending Page	125
Page Count	5
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 1, Jan (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.1058
Journal	IET Image Processing
Publisher Date	2017-10-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Angular Error Biased Colours Canonical White Light Colour Cast Colour Constancy Dataset Colour-biased Image Computer Vision Computer Vision And Image Processing Technique Deep Nonnegative Matrix Factorisation DeepNMF Method Diagonal Model Environmental Light Source Image Classification Image Colour Analysis Image Recognition Input Matrix Matrix Decomposition Mean Pooling Natural Image Illuminant Estimation Object Classification Object Recognition
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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