Optical MEMS image enhancement with sparse signal representation

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

This paper describes a complete low-complexity imaging system based on a single MEMS scanning mirror and a single photodetector, together with customized image enhancement algorithms based on sparse signal representation. Due to very low complexity of our developped optical set-up for image acquisition, resulting images suffer visible artifacts. We propose an iterative denoising-deblurring algorithm for image enhancement, which offers significant improvement over wavelet denoising with soft-thresholding. Several image enhancement algorithms are compared using the blind image quality indices (BIQI) as well as visual experience.
Original languageEnglish
Title of host publication2011 IEEE International conference on acoustics, speech and signal processing
Place of PublicationNew York
PublisherIEEE
Pages1109-1112
Number of pages4
ISBN (Print)9781457705397
DOIs
Publication statusPublished - 2011
EventIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) - Prague, Czech Republic
Duration: 22 May 201127 May 2011

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
CountryCzech Republic
CityPrague
Period22/05/1127/05/11

Fingerprint

MOEMS
Image enhancement
Image acquisition
Photodetectors
Imaging systems
Image quality
MEMS
Mirrors
Scanning

Keywords

  • sparse representation
  • image enhancement
  • optical
  • mems image enhancement
  • sparse signal representation

Cite this

Zhang, G. C., Li, L., Stankovic, V., Stankovic, L., & Uttamchandani, D. (2011). Optical MEMS image enhancement with sparse signal representation. In 2011 IEEE International conference on acoustics, speech and signal processing (pp. 1109-1112). New York: IEEE. https://doi.org/10.1109/ICASSP.2011.5946602
Zhang, G. C. ; Li, L. ; Stankovic, V. ; Stankovic, L. ; Uttamchandani, D. / Optical MEMS image enhancement with sparse signal representation. 2011 IEEE International conference on acoustics, speech and signal processing. New York : IEEE, 2011. pp. 1109-1112
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title = "Optical MEMS image enhancement with sparse signal representation",
abstract = "This paper describes a complete low-complexity imaging system based on a single MEMS scanning mirror and a single photodetector, together with customized image enhancement algorithms based on sparse signal representation. Due to very low complexity of our developped optical set-up for image acquisition, resulting images suffer visible artifacts. We propose an iterative denoising-deblurring algorithm for image enhancement, which offers significant improvement over wavelet denoising with soft-thresholding. Several image enhancement algorithms are compared using the blind image quality indices (BIQI) as well as visual experience.",
keywords = "sparse representation, image enhancement, optical, mems image enhancement, sparse signal representation",
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Zhang, GC, Li, L, Stankovic, V, Stankovic, L & Uttamchandani, D 2011, Optical MEMS image enhancement with sparse signal representation. in 2011 IEEE International conference on acoustics, speech and signal processing. IEEE, New York, pp. 1109-1112, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) , Prague, Czech Republic, 22/05/11. https://doi.org/10.1109/ICASSP.2011.5946602

Optical MEMS image enhancement with sparse signal representation. / Zhang, G. C.; Li, L.; Stankovic, V.; Stankovic, L.; Uttamchandani, D.

2011 IEEE International conference on acoustics, speech and signal processing. New York : IEEE, 2011. p. 1109-1112.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

TY - GEN

T1 - Optical MEMS image enhancement with sparse signal representation

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Zhang GC, Li L, Stankovic V, Stankovic L, Uttamchandani D. Optical MEMS image enhancement with sparse signal representation. In 2011 IEEE International conference on acoustics, speech and signal processing. New York: IEEE. 2011. p. 1109-1112 https://doi.org/10.1109/ICASSP.2011.5946602