Regular Articles

Local feature descriptor invariant to monotonic illumination changes

[+] Author Affiliations
Pu Yan, Dong Liang, Jun Tang, Ming Zhu

Anhui University, School of Electronics and Information Engineering, No. 111 Jiulong Road, Hefei 230601, China

J. Electron. Imaging. 25(1), 013023 (Feb 03, 2016). doi:10.1117/1.JEI.25.1.013023
History: Received June 15, 2015; Accepted December 17, 2015
Text Size: A A A

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.

Figures in this Article
© 2015 SPIE and IS&T

Topics

Matrices ; Sensors

Citation

Pu Yan ; Dong Liang ; Jun Tang and Ming Zhu
"Local feature descriptor invariant to monotonic illumination changes", J. Electron. Imaging. 25(1), 013023 (Feb 03, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.1.013023


Tables

Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.