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.
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He, Q., Chu, CH.H. (2007). Intrinsic Images by Fisher Linear Discriminant. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_34
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DOI: https://doi.org/10.1007/978-3-540-76856-2_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76855-5
Online ISBN: 978-3-540-76856-2
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