NDLI: Probabilistic Gaussian similarity-based local colour transfer

Content Provider	IET Digital Library
Author	Heo, Y. S. Jung, H. Y.
Abstract	A simple and robust probabilistic colour transfer method using feature matching and Gaussian mixture model (GMM)-based soft segmentation is proposed. Traditional colour transfer methods using GMM colour model require proper Gaussian matching where the euclidean distances of mean colours and positions of spatially overlapping regions are usually used as a matching measure. It is, however, difficult for these methods to find proper Gaussian matches for images taken from different illuminations, brightnesses, view-points as well as different camera types and settings. This is troublesome since incorrect matches result in unwanted colour artefacts. To cope with this problem, a new Gaussian similarity measure and probabilistic colour transfer formulation are presented. Experimental results demonstrate that, compared with previous methods, more robust and proper colour transfer results are generated for images taken from different conditions.
Starting Page	1120
Ending Page	1122
Page Count	3
ISSN	00135194
Volume Number	52
e-ISSN	1350911X
Issue Number	Issue 13, Jun (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/52/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.0632
Journal	Electronics Letters
Publisher Date	2016-05-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Brightness Brightnesses Camera Settings Camera Types Computational Geometry Computer Vision And Image Processing Technique Euclidean Distances Feature Extraction Feature Matching Gaussian Matching Gaussian Mixture Model-based Soft Segmentation Gaussian Processes Gaussian Similarity Measure GMM-based Soft Segmentation Illuminations Image Colour Analysis Image Matching Image Recognition Image Segmentation Image Sonsor Lighting Mean Colours Mixture Model Probabilistic Gaussian Similarity-based Local Colour Transfer Method Probability Statistics Unwanted Colour Artefacts View-Point
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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