OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 52, Iss. 8 — Mar. 10, 2013
  • pp: 1646–1654

Compression of infrared imagery sequences containing a slow-moving point target, part II

Revital Huber-Shalem, Ofer Hadar, Stanley R. Rotman, and Merav Huber-Lerner  »View Author Affiliations


Applied Optics, Vol. 52, Issue 8, pp. 1646-1654 (2013)
http://dx.doi.org/10.1364/AO.52.001646


View Full Text Article

Acrobat PDF (581 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research concentrates on slow-moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. Because transmitting IR imagery sequences to a base unit or storing them consumes considerable time and resources, a compression method that maintains the point-target detection capabilities is highly desirable. In our previous work, we introduced two temporal compression methods that preserve the temporal profile properties of the point target in the form of discrete cosine transform (DCT) quantization and parabola fit. In the present work, we extend the compression task method of DCT quantization by applying spatial compression over the temporally compressed coefficients, which is followed by bit encoding. We evaluate the proposed compression method using a signal-to-noise ratio (SNR)–based measure for point target detection and find that it yields better results than the compression standard H.264. Furthermore, we introduce an automatic detection algorithm that extracts the target location from the SNR scores image, which is acquired during the evaluation process and has a probability of detection and a probability of false alarm close to those of the original sequences. We previously determined that it is necessary to establish a minimal noise level in the SNR-based measure to compensate for smoothing that is induced by the compression. Here, the noise level calculation process is modified in order to allow detection of targets traversing all background types.

© 2013 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.4999) Image processing : Pattern recognition, target tracking

ToC Category:
Image Processing

History
Original Manuscript: November 2, 2012
Revised Manuscript: January 26, 2013
Manuscript Accepted: February 7, 2013
Published: March 7, 2013

Citation
Revital Huber-Shalem, Ofer Hadar, Stanley R. Rotman, and Merav Huber-Lerner, "Compression of infrared imagery sequences containing a slow-moving point target, part II," Appl. Opt. 52, 1646-1654 (2013)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-52-8-1646

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited