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Proceedings Paper

Compressive optical remote sensing via fractal classification
Author(s): Quan-sen Sun; Ji-xin Liu
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Paper Abstract

High resolution and large field of view are two major development trends in optical remote sensing imaging. But these trends will cause the difficult problem of mass data processing and remote sensor design under the limitation of conventional sampling method. Therefore, we will propose a novel optical remote sensing imaging method based on compressed sensing theory and fractal feature extraction in this study. We could utilize the result of fractal classification to realize the selectable partitioned image recovery with undersampling measurement. The two experiments illustrate the availability and feasibility of this new method.

Paper Details

Date Published: 5 November 2015
PDF: 9 pages
Proc. SPIE 9795, Selected Papers of the Photoelectronic Technology Committee Conferences held June–July 2015, 97950S (5 November 2015); doi: 10.1117/12.2211605
Show Author Affiliations
Quan-sen Sun, Nanjing Univ. of Science and Technology (China)
Ji-xin Liu, Nanjing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 9795:
Selected Papers of the Photoelectronic Technology Committee Conferences held June–July 2015
Shenggang Liu; Songlin Zhuang; Michael I. Petelin; Libin Xiang, Editor(s)

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