Efficient, low complexity encoding of multiple, blurred noisy downsampled images via distributed source coding principles

Matthew Gaubatz, Azadeh Vosoughi, Anna Scaglione, Sheila S. Hemami

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

1 Citation (Scopus)

Abstract

In a portable device, such as a digital camera, limitations on storage are an important consideration. In addition, due to constraints on the complexity of available hardware, image coding algorithms must be fairly simple in implementation. This work presents one such efficient method for coding multiple images of a scene, in a manner that complements a post-processing-based enhancement system. Super-resolution, image restoration and de-noising algorithms have demonstrated the ability to improve the quality of an image using multiple blurry, noisy copies of the same scene. This additional quality does not come without cost, however, since an image capture system must store each image. The proposed encoding scheme is derived from a general linear system model, and encodes multiple images of the same scene, with different amounts of blurring. It is also compared with a variety of methods based on current camera compression technology. For the tested images, this approach requires one-half the rate required by other methods at lower rates. In addition, for a small performance loss, it is essentially implementable without using any compression hardware.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
StatePublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Other

Other2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
CountryFrance
CityToulouse
Period5/14/065/19/06

Fingerprint

coding
Hardware
Digital cameras
Image reconstruction
Image coding
Linear systems
Cameras
Processing
hardware
Costs
blurring
digital cameras
image resolution
linear systems
restoration
complement
cameras
costs
augmentation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

Cite this

Gaubatz, M., Vosoughi, A., Scaglione, A., & Hemami, S. S. (2006). Efficient, low complexity encoding of multiple, blurred noisy downsampled images via distributed source coding principles. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 2). [1660280]

Efficient, low complexity encoding of multiple, blurred noisy downsampled images via distributed source coding principles. / Gaubatz, Matthew; Vosoughi, Azadeh; Scaglione, Anna; Hemami, Sheila S.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 2 2006. 1660280.

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

Gaubatz, M, Vosoughi, A, Scaglione, A & Hemami, SS 2006, Efficient, low complexity encoding of multiple, blurred noisy downsampled images via distributed source coding principles. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. vol. 2, 1660280, 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, Toulouse, France, 5/14/06.
Gaubatz M, Vosoughi A, Scaglione A, Hemami SS. Efficient, low complexity encoding of multiple, blurred noisy downsampled images via distributed source coding principles. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 2. 2006. 1660280
Gaubatz, Matthew ; Vosoughi, Azadeh ; Scaglione, Anna ; Hemami, Sheila S. / Efficient, low complexity encoding of multiple, blurred noisy downsampled images via distributed source coding principles. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 2 2006.
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