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Temporal compressive sensing for video

Publication ,  Conference
Llull, P; Yuan, X; Liao, X; Yang, J; Kittle, D; Carin, L; Sapiro, G; Brady, DJ
January 1, 2015

Video camera architects must design cameras capable of high-quality, dynamic event capture, while adhering to power and communications constraints. Though modern imagers are capable of both simultaneous spatial and temporal resolutions at micrometer and microsecond scales, the power required to sample at these rates is undesirable. The field of compressive sensing (CS) has recently suggested a solution to this design challenge. By exploiting physical-layer compression strategies, one may overlay the original scene with a coding sequence to sample at sub-Nyquist rates with virtually no additional power requirement. The underlying scene may be later estimated without significant loss of fidelity. In this chapter, we cover a variety of such strategies taken to improve an imager’s temporal resolution. Highlighting a new low-power acquisition paradigm, we show how a video sequence of high temporal resolution may be reconstructed from a single video frame taken with a low-framerate camera.

Duke Scholars

DOI

EISSN

2296-5017

ISSN

2296-5009

Publication Date

January 1, 2015

Issue

9783319160412

Start / End Page

41 / 74
 

Citation

APA
Chicago
ICMJE
MLA
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Llull, P., Yuan, X., Liao, X., Yang, J., Kittle, D., Carin, L., … Brady, D. J. (2015). Temporal compressive sensing for video (pp. 41–74). https://doi.org/10.1007/978-3-319-16042-9_2
Llull, P., X. Yuan, X. Liao, J. Yang, D. Kittle, L. Carin, G. Sapiro, and D. J. Brady. “Temporal compressive sensing for video,” 41–74, 2015. https://doi.org/10.1007/978-3-319-16042-9_2.
Llull P, Yuan X, Liao X, Yang J, Kittle D, Carin L, et al. Temporal compressive sensing for video. In 2015. p. 41–74.
Llull, P., et al. Temporal compressive sensing for video. no. 9783319160412, 2015, pp. 41–74. Scopus, doi:10.1007/978-3-319-16042-9_2.
Llull P, Yuan X, Liao X, Yang J, Kittle D, Carin L, Sapiro G, Brady DJ. Temporal compressive sensing for video. 2015. p. 41–74.

DOI

EISSN

2296-5017

ISSN

2296-5009

Publication Date

January 1, 2015

Issue

9783319160412

Start / End Page

41 / 74