Embedded polarizing filters to separate diffuse and specular reflection

Co-authors

Laurent Jospin and Gilles Baechler.


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Full text: 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 with different polarizations. In this paper, we investigate the

Shape from bandwidth: The 2-D orthogonal projection case

Co-authors

Benjamín Bejar Haro and Martin Vetterli.


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Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Run in browser (using binder), Infoscience.


Abstract

Could bandwidth – one of the most classic concepts in signal processing – have a new purpose? In this paper, we investigate the feasibility of using bandwidth to infer shape from a single image. As a first analysis, we limit our

Accurate image registration using approximate Strang-Fix and an application in super-resolution

Co-author

Pier Luigi Dragotti.


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


Abstract

Accurate registration is critical to most multi-channel signal processing setups, including image super-resolution. In this paper we use modern sampling theory to propose a new robust registration algorithm that works with arbitrary sampling kernels. The algorithm accurately approximates continuous-time Fourier coefficients from discrete-time samples. These Fourier coefficients can be used to

Quadtree Structured Image Approximation for Denoising and Interpolation

Co-author

Pier Luigi Dragotti.


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


Abstract

The success of many image restoration algorithms is often due to their ability to sparsely describe the original signal. Shukla proposed a compression algorithm, based on a sparse quadtree decomposition model, which could optimally represent piecewise polynomial images. In this paper, we adapt this model to the image restoration by changing

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