ArticleFrontiers in neurorobotics2026
PSRNet: a phase-guided frequency-domain structure reconstruction network for RGB-T salient object detection.
Article in Frontiers in neurorobotics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: RGB-T salient object detection remains challenging because visible and thermal features often show structural shifts, weak thermal boundaries, and background interference. Methods: This study proposes PSRNet, a phase-guided frequency-domain structure reconstruction network. RGB and thermal features are decomposed into amplitude and latent-phase components in the Fourier domain. Reliable cross-modal structural cues are aligned through amplitude-weighted phase consistency, and boundary-related high-frequency responses are reconstructed with a bounded Gaussian high-pass gate before adaptive phase-modulated fusion and multi-scale supervision. Results: On VT1000, PSRNet achieved an S-measure of 0.903, an MAE of 0.028, and an F-measure of 0.794 at threshold 0.80, with a boundary IoU of 0.862. Discussion: The results indicate improved structural preservation and boundary recovery under challenging RGB-T conditions.
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