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Sliced L2 Distance for Colour Grading

arXiv 2102.09297 ↗First posted 18 Feb 2021cs.CVcited by 0

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Abstract (arXiv)

We propose a new method with L2 distance that maps one N-dimensional distribution to another, taking into account available information about correspondences. We solve the high-dimensional problem in 1D space using an iterative projection approach. To show the potentials of this mapping, we apply it to colour transfer between two images that exhibit overlapped scenes. Experiments show quantitative and qualitative competitive results as compared with the state of the art colour transfer methods.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 28 references that are in the map. First posted on arXiv 18 Feb 2021.

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6 of 28 references.

References · 6

  1. 2013Regularized Discrete Optimal Transportcited by 54
  2. 2019Discriminator optimal transportcited by 25
  3. 2019Subspace Detours: Building Transport Plans that are Optimal on Subspace Projectionscited by 19
  4. 2017Shape Registration with Directional Datacited by 1
  5. 2020Patch based Colour Transfer using SIFT Flowcited by 1
  6. 2020Iterative Nadaraya-Watson Distribution Transfer for Colour Gradingcited by 1

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