PsSR: Hybrid Path Selection Mechanism for Efficient Image Super-Resolution

In practical applications, large images are processed in patches, many of which are simple and smooth, making them suitable for lighter network processing. This paper proposes a hybrid path selection mechanism that enables the dynamic routing of patches through the network, achieving a balance between accuracy and computational efficiency. The proposed method develops a dual-branch architecture, in which the two branches keep the same structural design, but differ in the number of channels. An efficient classification module is integrated for directing patches to the appropriate branches within the model. In addition, within each branch, we introduce an early exit strategy to further reduce the calculation cost. Subsequently, we enhance the restoration capabilities of the lightweight branch through channel and spatial feature distillation. Experimental results demonstrate that our Hybrid Path Selection based Super-Resolution (PsSR) mechanism effectively reduces computational costs while preserving the integrity of the backbone performance.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10888551
Citations
1
Primary Topic
Advanced Image Processing Techniques
Type
article
Field-Weighted Citation Impact
1.28

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article

PsSR: Hybrid Path Selection Mechanism for Efficient Image Super-Resolution

Zhong‐Qiu Zhao, Cheng Ding, Yang Zhao
1 citations
Advanced Image Processing Techniques
1.28
article

PsSR: Hybrid Path Selection Mechanism for Efficient Image Super-Resolution

Zhong‐Qiu Zhao, Cheng Ding, Yang Zhao
article en
1 citations

Abstract

In practical applications, large images are processed in patches, many of which are simple and smooth, making them suitable for lighter network processing. This paper proposes a hybrid path selection mechanism that enables the dynamic routing of patches through the network, achieving a balance between accuracy and computational efficiency. The proposed method develops a dual-branch architecture, in which the two branches keep the same structural design, but differ in the number of channels. An efficient classification module is integrated for directing patches to the appropriate branches within the model. In addition, within each branch, we introduce an early exit strategy to further reduce the calculation cost. Subsequently, we enhance the restoration capabilities of the lightweight branch through channel and spatial feature distillation. Experimental results demonstrate that our Hybrid Path Selection based Super-Resolution (PsSR) mechanism effectively reduces computational costs while preserving the integrity of the backbone performance.

Hefei University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 23%
Advanced Image Processing Techniques
1.28
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PsSR: Hybrid Path Selection Mechanism for Efficient Image Super-Resolution — Zhong‐Qiu Zhao, Cheng Ding, et al. · (2025) | TGRS Research Map | TGRS