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Proceedings Paper

A mosaic approach for unmanned airship remote sensing images based on compressive sensing
Author(s): Jilian Yang; Aiwu Zhang; Weidong Sun
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Paper Abstract

The recently-emerged compressive sensing (CS) theory goes against the Nyquist-Shannon (NS) sampling theory and shows that signals can be recovered from far fewer samples than what the NS sampling theorem states. In this paper, to solve the problems in image fusion step of the full-scene image mosaic for the multiple images acquired by a low-altitude unmanned airship, a novel information mutual complement (IMC) model based on CS theory is proposed. IMC model rests on a similar concept that was termed as the joint sparsity models (JSMs) in distributed compressive sensing (DCS) theory, but the measurement matrix in our IMC model is rearranged in order for the multiple images to be reconstructed as one combination. The experimental results of the BP and TSW-CS algorithm with our IMC model certified the effectiveness and adaptability of this proposed approach, and demonstrated that it is possible to substantially reduce the measurement rates of the signal ensemble with good performance in the compressive domain.

Paper Details

Date Published: 23 November 2011
PDF: 7 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80061C (23 November 2011); doi: 10.1117/12.902282
Show Author Affiliations
Jilian Yang, Tsinghua Univ. (China)
Aiwu Zhang, Capital Normal Univ. (China)
Weidong Sun, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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