Level set estimation from compressive measurements using box constrained total variation regularization

Akshay Soni; Jarvis D Haupt

doi:10.1109/ICIP.2012.6467424

Level set estimation from compressive measurements using box constrained total variation regularization

Akshay Soni, Jarvis D Haupt

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Estimating the level set of a signal from measurements is a task that arises in a variety of fields, including medical imaging, astronomy, and digital elevation mapping. Motivated by scenarios where accurate and complete measurements of the signal may not available, we examine here a simple procedure for estimating the level set of a signal from highly incomplete measurements, which may additionally be corrupted by additive noise. The proposed procedure is based on box-constrained Total Variation (TV) regularization. We demonstrate the performance of our approach, relative to existing state-of-the-art techniques for level set estimation from compressive measurements, via several simulation examples.

Original language	English (US)
Title of host publication	2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages	2573-2576
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2012.6467424
State	Published - Dec 1 2012
Event	2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States Duration: Sep 30 2012 → Oct 3 2012

Other

Other	2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country	United States
City	Lake Buena Vista, FL
Period	9/30/12 → 10/3/12

Keywords

Compressive sensing
FISTA
TV norm

Access

10.1109/ICIP.2012.6467424

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Soni, A & Haupt, JD 2012, Level set estimation from compressive measurements using box constrained total variation regularization. in 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings., 6467424, pp. 2573-2576, 2012 19th IEEE International Conference on Image Processing, ICIP 2012, Lake Buena Vista, FL, United States, 9/30/12. https://doi.org/10.1109/ICIP.2012.6467424

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