Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection

Chang, Yan; Ma, Decao; Yang, Qisong; Li, Shaopeng; Zhang, Daqiao

doi:10.3390/rs17203457

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Open AccessArticle

Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection

by

Yan Chang

,

Decao Ma

^*

,

Qisong Yang

,

Shaopeng Li

and

Daqiao Zhang

PLA Rocket Force University of Engineering, Xi’an 710025, China

^*

Author to whom correspondence should be addressed.

Remote Sens. 2025, 17(20), 3457; https://doi.org/10.3390/rs17203457

Submission received: 20 August 2025 / Revised: 9 October 2025 / Accepted: 10 October 2025 / Published: 16 October 2025

(This article belongs to the Section AI Remote Sensing)

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Abstract

With the development of infrared remote sensing technology and the deployment of satellite constellations, infrared video from orbital platforms is playing an increasingly important role in airborne target surveillance. However, due to the limitations of remote sensing imaging, the aerial targets in such videos are often small in scale, low in contrast, and slow in movement, making them difficult to detect in complex backgrounds. In this paper, we propose a novel detection network that integrates inter-frame residual guidance with spatio-temporal feature enhancement to address the challenge of small object detection in infrared satellite video. This method first extracts residual features to highlight motion-sensitive regions, then uses a dual-branch structure to encode spatial semantics and temporal evolution, and then fuses them deeply through a multi-scale feature enhancement module. Extensive experiments show that this method outperforms mainstream methods in terms on various infrared small target video datasets, and has good robustness under low-signal-to-noise-ratio conditions.

Keywords: infrared video; satellite remote sensing; small object detection; inter-frame residual; spatio-temporal feature fusion

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MDPI and ACS Style

Chang, Y.; Ma, D.; Yang, Q.; Li, S.; Zhang, D. Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection. Remote Sens. 2025, 17, 3457. https://doi.org/10.3390/rs17203457

AMA Style

Chang Y, Ma D, Yang Q, Li S, Zhang D. Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection. Remote Sensing. 2025; 17(20):3457. https://doi.org/10.3390/rs17203457

Chicago/Turabian Style

Chang, Yan, Decao Ma, Qisong Yang, Shaopeng Li, and Daqiao Zhang. 2025. "Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection" Remote Sensing 17, no. 20: 3457. https://doi.org/10.3390/rs17203457

APA Style

Chang, Y., Ma, D., Yang, Q., Li, S., & Zhang, D. (2025). Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection. Remote Sensing, 17(20), 3457. https://doi.org/10.3390/rs17203457

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Spatio-Temporal Residual Attention Network for Satellite-Based Infrared Small Target Detection

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