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Recoding Color Transfer as A Color Homography
Author(s) -
Han Gong,
Graham D. Finlayson,
Robert B. Fisher
Publication year - 2016
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.30.17
Subject(s) - computer vision , artificial intelligence , color balance , computer science , color constancy , chromaticity , homography , color histogram , color model , color image , color quantization , color normalization , color space , mathematics , image processing , image (mathematics) , statistics , projective test , projective space
Color transfer is an image editing process that adjusts the colors of a picture to match a target picture's color theme. A natural color transfer not only matches the color styles but also prevents after-transfer artifacts due to image compression, noise, and gradient smoothness change. The recently discovered color homography theorem proves that colors across a change in photometric viewing condition are related by a homography. In this paper, we propose a color-homography-based color transfer decomposition which encodes color transfer as a combination of chromaticity shift and shading adjustment. A powerful form of shading adjustment is shown to be a global shading curve by which the same shading homography can be applied elsewhere. Our experiments show that the proposed color transfer decomposition provides a very close approximation to many popular color transfer methods. The advantage of our approach is that the learned color transfer can be applied to many other images (e.g. other frames in a video), instead of a frame-to-frame basis. We demonstrate two applications for color transfer enhancement and video color grading re-application. This simple model of color transfer is also important for future color transfer algorithm design.

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