Multi-channel Time Encoding for Improved Reconstruction of Bandlimited Signals

Co-authors

Karen Adam and Martin Vetterli.


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Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Infoscience.


Abstract

Traditional sampling involves encoding a signal through (time, value)-pairs. In contrast, time encoding machines (TEMs) characterize a signal by recording time points which depend on the integral of the signal over time. We study multi-channel TEMs where channels have shifted values for their integrators. We show that M channels can enable recovery of bandlimited signals with

Embedded polarizing filters to separate diffuse and specular reflection

Co-authors

Laurent Jospin and Gilles Baechler.


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Full text: View at publisher, Arxiv.
Cite: Bibtex.
Code: Will appear shortly.


Abstract

Polarizing filters provide a powerful way to separate diffuse and specular reflection; however, traditional methods rely on several captures and require proper alignment of the filters. Recently, camera manufacturers have proposed to embed polarizing micro-filters in front of the sensor, creating a mosaic of pixels

Combining Range and Direction for Improved Localization

Co-authors

Gilles Baechler, Frederike Dümbgen, Golnoosh Elhami, Miranda Krekovic, Robin Scheibler and Martin Vetterli.


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Full text: Infoscience.
Cite: Bibtex.
Code: GitHub.


Abstract

Self-localization of nodes in a sensor network is typically achieved using either range or direction measurements; in this paper, we show that a constructive combination of both improves the estimation. We propose two localization algorithms that make use of the differences between the sensors’

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