Specular free spectral imaging using orthogonal subspace projection
Date
2006
Authors
Fu, Zhouyu
Tan, Robby
Caelli, Terry
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
Specularity is an important issue in computer vision. Many algorithms have been proposed to remove highlights for color images. However, to our knowledge, no work has been done so far which specifically handles highlights in spectral imaging. In this paper, we introduce a specular invariant representation for hyperspectral images based on the dichromatic model and orthogonal subspace projection. It is a simple one step algorithm which only involves pixel-level operations, thus it does not require any segmentation. Nor does it require any pre/postprocessing or explicit spectral normalization. Importantly, unlike the previous methods for color images, it can be theoretically extended to handle highlights caused by multicolored illuminations. Experimental results demonstrate the effectiveness of our algorithm.
Description
Keywords
Keywords: Algorithms; Image analysis; Image segmentation; Mathematical models; Dichromatic model; Subspace projection; Imaging techniques
Citation
Collections
Source
Proceedings of the 18th International Conference on Pattern Recognition
Type
Conference paper