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Compressive Sensing

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Computer Vision

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Synonyms

Compressed sensing

Related Concepts

Dimensionality Reduction

Definition

Compressed sensing refers to parsimonious sensing, recovery, and processing of signals under a sparse prior.

Background

The design of conventional sensors is based heavily on the Shannon-Nyquist sampling theorem which states that a signal x band limited to W Hz is determined completely by its discrete time samples provided the sampling rate is greater than 2Wsamples per second. This theorem is at the heart of modern signal processing as it enables signal processing in the discrete time or digital domain without any loss of information. However, for many applications, the Nyquist sampling rate is high as well as redundant and unnecessary. As a motivating example, in modern cameras, the high resolution of the CCD sensor reflects the large amount of data sensed to capture an image. A 10 megapixel camera, in effect, takes 10 million linear measurements of the scene. Yet, almost immediately after capture,...

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Author information

Authors and Affiliations

  1. ECE Department, Rice University, Houston, TX, USA

    Aswin C. Sankaranarayanan

  2. Department of Electrical and Computer Engineering, Rice University, 2028 Duncan Hal, Houston, TX, USA

    Richard G. Baraniuk

Authors
  1. Aswin C. Sankaranarayanan
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  2. Richard G. Baraniuk
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Editor information

Editors and Affiliations

  1. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

    Katsushi Ikeuchi

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Sankaranarayanan, A.C., Baraniuk, R.G. (2014). Compressive Sensing. In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_647

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