JOURNAL ARTICLE

Infrared Small Target Detection Based on Morphological Feature Extraction

Abstract

Infrared (IR) small target detection of low signal-to-noise ratio (SNR) is a very meaningful and challenging subject in detecting and tracking system. Therefore, an effective method is proposed in this paper. First of all, a morphological feature extraction method is used to reconstruct a new image that the small target is disappeared, then the original image and the reconstruction image are made difference as preprocessed image. In this way, important spatial information can be extracted well in IR image. Then, a low-rank and sparse decomposition method is employed to obtain the background image and the target image respectively, the target separation can be enhanced and the background clutter can be suppressed simultaneously. Finally, the obtained target image is segmented by a simple adaptive segmentation method. The experimental results indicate that the proposed method is of great improvement compared with several existing methods, what's more, it can achieve the highest SNR among these methods.

Keywords:
Artificial intelligence Computer science Clutter Computer vision Pattern recognition (psychology) Feature extraction Feature detection (computer vision) Image segmentation Feature (linguistics) Segmentation Image (mathematics) Image processing Radar

Metrics

8
Cited By
1.27
FWCI (Field Weighted Citation Impact)
10
Refs
0.87
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
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology

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