Color Transfer between Images

By E. Reinhard, Michael Ashikhmin, Bruce Gooch, Peter Shirley. 2001

3,172 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition

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In Atomic and Molecular Physics, and Optics

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Citations in the corpus

Image-to-Image Translation with Conditional Adversarial Networks (2016, background): “Color histogram matching is a common problem in image processing [46], and PixelGANs may be a promising lightweight solution.”
Generative Visual Manipulation on the Natural Image Manifold (2016, background): “Examples of basic editing include changing the color properties of an image either globally [6] or locally [7].”
Deep Photo Style Transfer (2017, methodology): “We compared against several global methods in our second study: Reinhard’s statistics transfer [12],”
Enhancing Photorealism Enhancement (2021, background): “[47] (Color Transfer) and the color distribution transfer Fig.”
Fast image and video colorization using chrominance blending (2006, background): “Welsh et al. [28], inspired by work of Reinhard et al. [21] and Hertzmann et al. [11], extended this idea by matching luminance and texture rather than just the grayscale values.”
Unsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks (2017, background): “On the other hand, researches on image stylization [4, 5, 6, 7, 8], that address instance-level visual attribute transfer have drawn signiﬁcant amount of attention recently.”
Gated Fusion Network for Single Image Dehazing (2018, methodology): “In this paper, we use the gray world assumption [26] based technique.”
Staingan: Stain Style Transfer for Digital Histological Images (2018, methodology): “Our proposed StainGAN method shows a relative improvement of ( 80% , 36% , 22% , 15% , and 3% ) on AUC over the Un-normalized, Reinhard, Macenko, Khan, and Vahadane, respectively.”
Automated colour grading using colour distribution transfer (2007, background): “To deal with this issue a simple solution [1,2,17] is to manually select swatches in both pictures and thus associate colour clusters corresponding to the same content.”
Colorization by example (2005, background): “[RAGS01] describe an automatic system for transferring the color pallet from one color image to another.”
Photographic tone reproduction for digital images (2002, methodology): “Because his operator includes color correction as well as dynamic range reduction, we have additionally color corrected our tone-mapped image (Figure 13) using the method presented in [Reinhard et al. 2001].”
Semantic photo manipulation with a generative image prior (2019, methodology): “Example applications include color adjustment [An and Pellacini 2008; Levin et al. 2004; Reinhard et al. 2001; Xue et al. 2012], tone mapping [Durand and Dorsey 2002], image warping [Avidan and Shamir 2007], image blending [Pérez et al. 2003; Tao et al. 2010], or image reshuffling [Barnes et al.…”
Transfusive image manipulation (2012, methodology): “, in case of varying exposure, we employed the method of Reinhard et al. [2001], utilizing our per-weight bias and gain estimation.”
Local color transfer via probabilistic segmentation by expectation-maximization (2005, background): “[9] first performed global color transfer according to Eqn.”
EditGAN: High-Precision Semantic Image Editing (2021, background): “Image Editing has a long history in computer vision and graphics, as well as machine learning [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 18, 11, 28, 41, 42, 16].”