Noise correlation-based adaptive polarimetric image representation for contrast enhancement of a polarized beacon in fog

Swapnesh Panigrahi; Julien Fade; Mehdi Alouini

doi:10.1117/12.2195216

15 October 2015 Noise correlation-based adaptive polarimetric image representation for contrast enhancement of a polarized beacon in fog

Swapnesh Panigrahi, Julien Fade, Mehdi Alouini

Author Affiliations +

Proceedings Volume 9643, Image and Signal Processing for Remote Sensing XXI; 96430C (2015) https://doi.org/10.1117/12.2195216
Event: SPIE Remote Sensing, 2015, Toulouse, France

Abstract

We show the use of a simplified snapshot polarimetric camera along with an adaptive image processing for optimal detection of a polarized light beacon through fog. The adaptive representation is derived using theoretical noise analysis of the data at hand and is shown to be optimal in the Maximum likelihood sense. We report that the contrast enhancing optimal representation that depends on the background noise correlation differs in general from standard representations like polarimetric difference image or polarization filtered image. Lastly, we discuss a detection strategy to reduce the false positive counts.

Citation Download Citation

Swapnesh Panigrahi, Julien Fade, and Mehdi Alouini "Noise correlation-based adaptive polarimetric image representation for contrast enhancement of a polarized beacon in fog", Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 96430C (15 October 2015); https://doi.org/10.1117/12.2195216

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