Compressive optical remote sensing via fractal classification

Quan-sen Sun; Ji-xin Liu

doi:10.1117/12.2211605

5 November 2015 Compressive optical remote sensing via fractal classification

Quan-sen Sun, Ji-xin Liu

Proceedings Volume 9795, Selected Papers of the Photoelectronic Technology Committee Conferences held June–July 2015; 97950S (2015) https://doi.org/10.1117/12.2211605
Event: Selected Proceedings of the Photoelectronic Technology Committee Conferences held June-July 2015, 2015, Hefei, Suzhou, and Harbin, China

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.

Citation Download Citation

Quan-sen Sun and Ji-xin Liu "Compressive optical remote sensing via fractal classification", Proc. SPIE 9795, Selected Papers of the Photoelectronic Technology Committee Conferences held June–July 2015, 97950S (5 November 2015); https://doi.org/10.1117/12.2211605

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KEYWORDS

Fractal analysis

Remote sensing

Image processing

Image resolution

Image classification

Optical imaging

Feature extraction

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