Contrasted statistical processing algorithm for obtaining improved target detection performances in IR cluttered environment

Zeev Zalevsky, David Mendlovic, Ehud Rivlin, Stanley Rotman

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper presents a contrasted statistical processing approach to obtain improved probabilities of false alarm when performing automatic target detection. The technique is based upon analyzing each sector of the image and comparing it with surrounding windows in which the desired statistical property is calculated. The contrast of the statistical property is extracted using the prediction or the prediction-correction equations. The contrast of the statistical property is shown to be a good discriminator of the target from its background allowing the reduction of the detection threshold applied over the stationary region while maintaining a constant false alarm probability.

Original languageEnglish
Pages (from-to)801-812
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3808
StatePublished - 1999
Externally publishedYes
EventProceedings of the 1999 Applications of Digital Image Processing XXII - Denver, CO, USA
Duration: 20 Jul 199923 Jul 1999

Fingerprint

Dive into the research topics of 'Contrasted statistical processing algorithm for obtaining improved target detection performances in IR cluttered environment'. Together they form a unique fingerprint.

Cite this