Optimal Transportation for Example-Guided Color Transfer

In this paper, we propose an image completion algorithm based on dense correspondence between the input image and an exemplar image retrieved from the Internet. Contrary to traditional methods which register two images according to sparse correspondence, in this paper, we propose a hierarchical PatchMatch method that progressively estimates a dense correspondence, which is able to capture small deformations between images. The estimated dense correspondence has usually large occlusion areas that correspond to the regions to be completed. A nearest neighbor field (NNF) interpolation algorithm interpolates a smooth and accurate NNF over the occluded region. Given the calculated NNF, the correct image content from the exemplar image is transferred to the input image. Finally, as there could be a color difference between the completed content and the input image, a color correction algorithm is applied to remove the visual artifacts. Numerical results show that our proposed image completion method can achieve photo realistic image completion results.

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“…Different from the color transfer methods [52], [53] where color correspondences are not available, pixel-wise color cor-…”

Section: Color Correctionmentioning

confidence: 99%

Photo Realistic Image Completion via Dense Correspondence

Huang

Dragotti

2018

IEEE Trans. on Image Process.

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“…The proposed work equally works well for the video also. [6] The other novel method of color transfer was also studied which also involves feature detection along with color transfer. The approach is more cluster based method of style transfer.…”

Section: Literature Surveymentioning

confidence: 99%

Image Textural Style Transfer using Neural Network

Bhatnagar¹,

Upadhyay²,

Gupta³

et al. 2017

IJARCSSE

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Abstract-In this survey paper, the purpose was to present the context aware algorithm based textural style transfer based on sporadic representation of texture fusion. The ideology behind this is to blend the style which is identified from a reference image to a source image, while the scenic attributes of the source image are conserved. The sporadic representation focuses on the extraction of the texture or style from a reference or example image(s). The actual fusion takes place of the extracted style component with the source image where the settings are optimized to conserve the true scene structure. Here, the textural style transfer is performed automatically without the required knowledge of user interest.

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“…An example result and the effect of an increasing number of iterations can be seen in Figure 7. Instead, Frigo et al [FSDH14] pose the colour transfer problem as one of determining an optimal transport.…”

Section: Colour Ttransfer As a 3d Problemmentioning

confidence: 99%

Colour Mapping: A Review of Recent Methods, Extensions and Applications

Faridul

Pouli

Chamaret

et al. 2015

Computer Graphics Forum

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The objective of colour mapping or colour transfer methods is to recolour a given image or video by deriving a mapping between that image and another image serving as a reference. These methods have received considerable attention in recent years, both in academic literature and industrial applications. Methods for recolouring images have often appeared under the labels of colour correction, colour transfer or colour balancing, to name a few, but their goal is always the same: mapping the colours of one image to another. In this paper, we present a comprehensive overview of these methods and offer a classification of current solutions depending not only on their algorithmic formulation but also their range of applications. We also provide a new dataset and a novel evaluation technique called 'evaluation by colour mapping roundtrip'. We discuss the relative merit of each class of techniques through examples and show how colour mapping solutions can have been applied to a diverse range of problems.

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Optimal Transportation for Example-Guided Color Transfer

Cited by 33 publications

References 24 publications

Photo Realistic Image Completion via Dense Correspondence

Photo Realistic Image Completion via Dense Correspondence

Image Textural Style Transfer using Neural Network

Colour Mapping: A Review of Recent Methods, Extensions and Applications

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