Illumination and device invariant image stitching

We address the problem of compensating color differences in image stitching. We explicitly color correct input images before image stitching by leveraging sparse correspondences. Our approach is twofold. First, for each geometric correspondence, we locally collect and process color information to be...

Full description

Saved in:
Bibliographic Details
Main Authors: Faridul, Hasan Sheikh, Stauder, Jurgen, Tremeau, Alain
Format: Conference Proceeding
Language:English
Subjects:
Color
Computer vision
Image color analysis
Imaging
Lighting
Pattern recognition
Robustness
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We address the problem of compensating color differences in image stitching. We explicitly color correct input images before image stitching by leveraging sparse correspondences. Our approach is twofold. First, for each geometric correspondence, we locally collect and process color information to be robust against low accuracy in geometric correspondences. Second, for all collected colors, we fit a global model that compensates complex color changes. Despite complex cases between input images (changes of illumination condition and imaging devices) qualitative experiments show good stitching of our method compared to recent methods in the literature.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2014.7025010