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Open Access Fast and Robust Discrete Computational Imaging

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Computational imaging problems are of increasing importance in domains ranging from security to biology and medicine. In these problems computational techniques based on an imaging model are coupled with data inversion to create useful images. When the underlying desired property field itself is discrete, the corresponding discrete-valued inverse problems are extremely challenging and computationally expensive to solve because of their non-convex, enumerative nature. In this work we demonstrate a fast and robust solution approach based on a new variable splitting coupled with the alternating direction method of multipliers (ADMM) technique. This approach exploits sub-problems that can be solved using existing and fast techniques, such as graph-cut methods, and results in overall solutions of excellent quality. The method can exploit both Gaussian and Poisson noise models. We exercise the method on both binary and multi-label phantoms for challenging limited data tomographic reconstruction problems.
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Document Type: Research Article

Publication date: January 29, 2017

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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