JOURNAL ARTICLE

Infrared Moving Small-Target Detection Using Spatial–Temporal Local Difference Measure

Peng DuAskar Hamdulla

Year: 2019 Journal:   IEEE Geoscience and Remote Sensing Letters Vol: 17 (10)Pages: 1817-1821   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Effectiveness and false alarm (FA) suppression are key issues in infrared (IR) moving small-target detection. In this letter, we propose a novel spatial-temporal local difference measure (STLDM) algorithm to detect a moving IR small target. The method we propose involves three steps. First, we block off three frames in a certain range of time (temporal) domain. Next, in a 3-D spatial-temporal domain, we analyze the local grayscale intensity difference of the small targets moving between the three frames and calculate the difference between the grayscale intensity in the center area and the grayscale intensity in the eight directions in the area surrounding the target. Finally, we segment the small target in a detection result map. The results of our experiment demonstrate that our proposed STLDM method has a higher rate of detection of IR moving small targets, as well as fewer FAs than other existing methods.

Keywords:
Grayscale Artificial intelligence Computer science Computer vision False alarm Block (permutation group theory) Intensity (physics) Pattern recognition (psychology) Mathematics Pixel Optics Physics

Metrics

90
Cited By
7.92
FWCI (Field Weighted Citation Impact)
14
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Infrared Target Detection Methodologies
Physical Sciences →  Engineering →  Aerospace Engineering
Advanced Measurement and Detection Methods
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Thermography and Photoacoustic Techniques
Physical Sciences →  Engineering →  Mechanics of Materials
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