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Compressive sensing for active imaging in SWIR spectral range

: Paunescu, Gabriela; Lutzmann, Peter; Wegner, Daniel


Kamerman, G. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Electro-Optical Remote Sensing XII : 10-13 September 2018, Berlin, Germany
Bellingham, WA: SPIE, 2018 (Proceedings of SPIE 10796)
Paper 107960A, 8 pp.
Conference "Electro-Optical Remote Sensing" <12, 2018, Berlin>
Conference Paper
Fraunhofer IOSB ()

Compressive sensing (CS) is an imaging method that enables the replacement of expensive matrix detectors by small and cheap detectors with one or a few detector elements. A high-resolution image is realized from a series of individual single-value measurements. Each measurement consists of capturing the image from an object or a scene after coding by a well-defined pattern. The reconstruction of the high-resolution image requires a number of measurements significantly smaller than the number of full-frame image pixels. This is because most natural images may be sparsely coded, i.e. we may find an appropriate basis for which most coefficients are close to zero. This paper reports CS experiments under pulse laser illumination at 1.55 μm. The light collected from the observed scene is spatially modulated using a digital micromirror device (DMD) and projected onto a single-pixel detector. The applied binary patterns are generated using a Hadamard matrix. Different approaches for pattern selection have been implemented and compared.