A Variational Model for Histogram Transfer of Color Images

Papadakis, Nicolas; Provenzi, Edoardo; Caselles, Vicent

doi:10.1109/tip.2010.2095869

Cited by 58 publications

(69 citation statements)

References 14 publications

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“…Reinhard et al [24] proposed a simple and traditional statistics-based algorithm to transfer colors between two images, which was also extended by many researchers. Papadakis et al [25] proposed a variational model for color image histogram transfer, which used the energy functional minimization to finish the goal of transferring the image color style and maintaining the image geometry. Hristova et al [26] presented a style-aware robust color transfer method, which was based on the style feature clustering and the local chromatic adaptation transform.…”

Section: Statistics-based Color Transfermentioning

confidence: 99%

Histogram-Based Color Transfer for Image Stitching

Tian

Cohen

2017

J. Imaging

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Color inconsistency often exists between the images to be stitched and will reduce the visual quality of the stitching results. Color transfer plays an important role in image stitching. This kind of technique can produce corrected images which are color consistent. This paper presents a color transfer approach via histogram specification and global mapping. The proposed algorithm can make images share the same color style and obtain color consistency. There are four main steps in this algorithm. Firstly, overlapping regions between a reference image and a test image are obtained. Secondly, an exact histogram specification is conducted for the overlapping region in the test image using the histogram of the overlapping region in the reference image. Thirdly, a global mapping function is obtained by minimizing color differences with an iterative method. Lastly, the global mapping function is applied to the whole test image for producing a color-corrected image. Both the synthetic dataset and real dataset are tested. The experiments demonstrate that the proposed algorithm outperforms the compared methods both quantitatively and qualitatively.

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Section: Statistics-based Color Transfermentioning

confidence: 99%

Histogram-Based Color Transfer for Image Stitching

Tian

Cohen

2017

J. Imaging

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“…They include most of the variational formulations of the color transfer literature (see e.g. [5], [9], [17], [19], [20], [25]). …”

Section: Color Transfermentioning

confidence: 99%

Harmonic Flow for Histogram Matching

Batard

Bertalmío

2014

Image and Video Technology – PSIVT 2013 Workshops

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Abstract. We present a method to perform histogram matching between two color images based on the concept of harmonic mapping between Riemannian manifolds. The key idea is to associate the histogram of a color image to a Riemannian manifold. In this context, the energy of the matching between the two images is measured by the Dirichlet energy of the mapping between the Riemannian manifolds. Then, we assimilate optimal matchings to critical points of the Dirichlet energy. Such points are called harmonic maps. As there is no explicit expression for harmonic maps in general, we use a gradient descent flow with boundary condition to reach them, that we call harmonic flow. We present an application to color transfer, however many others applications can be envisaged using this general framework.

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“…However this method is limited to linear transforms. Papadakis et al [6] describe a variational formulation of the problem using cumulated histograms under colour conservation constraints, but provides 1-D transformations that is not suitable for our purpose.…”

Section: Colour Transfer Between Two Imagesmentioning

confidence: 99%