Color Homography: Theory and Applications

Graham Finlayson, Han Gong, Robert B. Fisher

Research output: Contribution to journalArticlepeer-review

Abstract

Images of co-planar points in 3-dimensional space taken from different camera positions are a homography apart. Homographies are at the heart of geometric methods in computer vision and are used in geometric camera calibration, 3D reconstruction, stereo vision and image mosaicking among other tasks. In this paper we show the surprising result that homographies are the apposite tool for relating image colors of the same scene when the capture conditions - illumination color, shading and device – change. Three applications of color homographies are investigated. First, we show that color calibration is correctly formulated as a homography problem. Second, we compare the chromaticity distributions of an image of colorful objects to a database of object chromaticity distributions using homography matching. In the color transfer problem, the colors in one image are mapped so that the resulting image color style matches that of a target image. We show that natural image color transfer can be re-interpreted as a color homography mapping. Experiments demonstrate that solving the color homography problem leads to more accurate calibration, improved color-based object recognition, and we present a new direction for developing natural color transfer algorithms.
Original languageEnglish
Pages (from-to)20-33
Number of pages14
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume41
Issue number1
Early online date4 Dec 2017
DOIs
Publication statusPublished - 1 Jan 2019

Fingerprint Dive into the research topics of 'Color Homography: Theory and Applications'. Together they form a unique fingerprint.

Cite this