Geometry-Aware RWKV for Heterogeneous Light Field Spatial Super-Resolution

Heterogeneous Light Field (LF) spatial Super-Resolution (SR) aims to significantly enhance the spatial resolution of LF imaging by integrating an extra 2D digital camera. Inspired by the Receptance Weighted Key Value (RWKV), a simple yet effective heterogeneous LF spatial SR method is proposed. Specifically, a texture transfer module with channel correlation is designed, which leverages a feature distillation strategy to transfer texture information from the high-resolution 2D image to the low-resolution LF image. Meanwhile, a spatial-angular rectification module is constructed to restore the spatial-angular coherence damaged in texture transfer. It employs geometry-aware RWKV to capture the intrinsic geometric structure of LFs. Experimental results show that the proposed method outperforms the state-of-the-art methods in both quantitative and qualitative comparisons, while achieving higher efficiency in terms of inference time and memory usage.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3555445
Citations
1
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
1.19
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article

Geometry-Aware RWKV for Heterogeneous Light Field Spatial Super-Resolution

Yeyao Chen, Haiyong Xu, Zean Chen, Linwei Zhu et al.
1 citations
IEEE Signal Processing Letters
Advanced Optical Sensing Technologies
1.19
article

Geometry-Aware RWKV for Heterogeneous Light Field Spatial Super-Resolution

Yeyao Chen, Haiyong Xu, Zean Chen, Linwei Zhu, Gangyi Jiang
article en
1 citations

Abstract

Heterogeneous Light Field (LF) spatial Super-Resolution (SR) aims to significantly enhance the spatial resolution of LF imaging by integrating an extra 2D digital camera. Inspired by the Receptance Weighted Key Value (RWKV), a simple yet effective heterogeneous LF spatial SR method is proposed. Specifically, a texture transfer module with channel correlation is designed, which leverages a feature distillation strategy to transfer texture information from the high-resolution 2D image to the low-resolution LF image. Meanwhile, a spatial-angular rectification module is constructed to restore the spatial-angular coherence damaged in texture transfer. It employs geometry-aware RWKV to capture the intrinsic geometric structure of LFs. Experimental results show that the proposed method outperforms the state-of-the-art methods in both quantitative and qualitative comparisons, while achieving higher efficiency in terms of inference time and memory usage.

IEEE Signal Processing LettersVol. 32
Ningbo University (CN), Chinese Academy of Sciences (CN), Shenzhen Institutes of Advanced Technology (CN)
Openalex Percentile: Top 23%
Advanced Optical Sensing Technologies
1.19
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Geometry-Aware RWKV for Heterogeneous Light Field Spatial Super-Resolution — Yeyao Chen, Haiyong Xu, et al. · IEEE Signal Processing Letters (2025) | TGRS Research Map | TGRS