Intrinsic images by Fisher linear discriminant

Authors:
Qiang He;Chee-Hung Henry Chu
Affiliations:
Department of Mathematics, Computer and Information Sciences, Mississippi Valley State University, Itta Bena, MS;The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Year:
2007

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Abstract

Intrinsic image decomposition is useful for improving the performance of such image understanding tasks as segmentation and object recognition. We present a new intrinsic image decomposition algorithm using the Fisher Linear Discriminant based on the assumptions of Lambertian surfaces, approximately Planckian lighting, and narrowband camera sensors. The Fisher Linear Discriminant not only considers the within-sensor data as convergent as possible but also treats the between-sensor data as separate as possible. The experimental results on real-world data show good performance of this algorithm.