Detecting and tracking moving objects in long-distance imaging through turbulent medium

Eli Chen, Oren Haik, Yitzhak Yitzhaky

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

The challenge of detecting and tracking moving objects in imaging throughout the atmosphere stems from the atmospheric turbulence effects that cause time-varying image shifts and blur. These phenomena significantly increase the miss and false detection rates in long-range horizontal imaging. An efficient method was developed, which is based on novel criteria for objects' spatio-temporal properties, to discriminate true from false detections, following an adaptive thresholding procedure for foreground detection and an activity-based false alarm likeliness masking. The method is demonstrated on significantly distorted videos and compared with state of the art methods, and shows better false alarm and miss detection rates.

Original languageEnglish
Pages (from-to)1181-1190
Number of pages10
JournalApplied Optics
Issue number6
DOIs
StatePublished - 20 Feb 2014

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