NDLI: Integrated tone and structure refinement for high-fidelity colour transfer

Content Provider	IET Digital Library
Author	Xie, Zhifeng Ding, Shouhong Sheng, Bin Ma, Lizhuang
Abstract	A high-fidelity colour transfer should align the colour distributions between images and meanwhile avoid the damage to the original structure. However, the traditional methods often fail to yield high-fidelity transfer results due to some existing tone and structure artefacts. In this study, the authors propose a new framework to effectively integrate the tone and structure refinements of colour transfer. They develop the ideas of image decomposition and gradient guidance to perform tone reconstruction while protecting original structure. Its overall flow includes the five key steps: tone clustering, structure extraction, structure optimisation, gradient-guided tone reconstruction, and structure restoration. Moreover, they propose an evaluation metric to measure the differences of tone and structure between images. They demonstrate the performance of the proposed method through a number of experiments in visual comparison and objective evaluation.
Starting Page	1281
Ending Page	1290
Page Count	10
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 12, Dec (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0668
Journal	IET Image Processing
Publisher Date	2017-08-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Colour Distribution Colour Transfer Structure Refinement Computer Vision And Image Processing Technique Damage Avoidance Gradient Guidance Gradient Method Gradient-guided Tone Reconstruction High-fidelity Colour Transfer Image Colour Analysis Image Decomposition Image Restoration Optical, Image And Video Signal Processing Optimisation Optimisation Technique Pattern Clustering Structure Artefacts Structure Extraction Structure Optimisation Structure Restoration Tone Clustering
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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