Local feature descriptor invariant to monotonic illumination changes

Pu Yan; Dong Liang; Jun Tang; Ming Zhu

doi:10.1117/1.JEI.25.1.013023

3 February 2016 Local feature descriptor invariant to monotonic illumination changes

Pu Yan, Dong Liang, Jun Tang, Ming Zhu

Author Affiliations +

Journal of Electronic Imaging, Vol. 25, Issue 1, 013023 (February 2016). https://doi.org/10.1117/1.JEI.25.1.013023

Abstract

This paper presents a monotonic invariant intensity descriptor (MIID) via spectral embedding and nonsubsampled contourlet transform (NSCT). To make the proposed descriptor discriminative, NSCT is used for the construction of multiple support regions. Specifically, the directed graph and the spectral feature vectors of the signless Laplacian matrix are exploited to construct the MIID. We theoretically demonstrate that the proposed descriptor is able to tackle monotonic illumination changes and many other geometric and photometric transformations. We conduct extensive experiments on the standard Oxford dataset and the complex illumination dataset to demonstrate the superiority of proposed descriptor over the existing state-of-the-art descriptors in dealing with image blur, viewpoint changes, illumination changes, and JPEG compression.

Citation Download Citation

Pu Yan, Dong Liang, Jun Tang, and Ming Zhu "Local feature descriptor invariant to monotonic illumination changes," Journal of Electronic Imaging 25(1), 013023 (3 February 2016). https://doi.org/10.1117/1.JEI.25.1.013023

Published: 3 February 2016

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