Double Layered-Background Removal Filter for Detecting Small Infrared Targets in Heterogenous Backgrounds

Title
Double Layered-Background Removal Filter for Detecting Small Infrared Targets in Heterogenous Backgrounds
Author(s)
김성호
Keywords
IR IMAGE SEQUENCES; DIM POINT-TARGETS; CLOUD CLUTTER; WAVELET TRANSFORM; ALGORITHM; SEA; TRACKING; FUSION
Issue Date
201101
Publisher
SPRINGER
Citation
JOURNAL OF INFRARED MILLIMETER AND TERAHERTZ WAVES, v.32, no.1, pp.79 - 101
Abstract
Detecting small targets is essential for mitigating the sea-based Infrared search and track (IRST) problem. It is easy to detect small targets in homogeneous backgrounds such as the sky. When targets are on the border line of heterogeneous backgrounds such as the horizon in the sky and sea surface, solving the problem of detection becomes difficult. This paper presents a novel spatial filtering method, called Double Layered-Background Removal Filter (DL-BRF), for achieving high detection rates and low false alarm rates. DL-BRF consists of a Modified-Mean Subtraction Filter (M-MSF) and a consecutive Local-Directional Background Removal Filter (L-DBRF). M-MSF enhances the target signal and reduces background noise. L-DBRF removes horizontal structures, which upgrade the signal-to-clutter ratio and background suppression factor. L-DBRF used after M-MSF enhances the synergistic performance of horizontal target detection. Additionally, the adaptive Hysteresis threshold-based scheme is a suitable detection method. We validate the superior performance of the proposed method via three types of evaluation tests, including a real test scenario.
URI
http://hdl.handle.net/YU.REPOSITORY/25735http://dx.doi.org/10.1007/s10762-010-9742-9
ISSN
1866-6892
Appears in Collections:
공과대학 > 전자공학과 > Articles
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