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Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal by Li, Xiangyu; Fan, Wanshu; Shen, Yue; Wang, Cong; Wang, Wei; Yang, Xin; Zhang, Qiang; Zhou, Dongsheng is a scholarly article available to read on EtoBox.

What is Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal about?

High-fidelity imaging is crucial for the successful safety supervision and intelligent deployment of vision-based measurement systems (VBMS). It ensures high-quality imaging in VBMS, which is fundamental for reliable visual measurement and analysis. However, imaging quality can be significantly impaired by adverse weather conditions, particularly rain, leading to blurred images and reduced contrast. Such impairments increase the risk of inaccurate evaluations and misinterpretations in VBMS. To address these limitations, we propose an Expectation Maximization Reconstruction Transformer (EMResformer) for single image rain streak removal. The EMResformer retains the key self-attention values for feature aggregation, enhancing local features to produce superior image reconstruction. Specifically, we propose an Expectation Maximization Block seamlessly integrated into the single image rain streak removal network, enhancing its ability to eliminate superfluous information and restore a cleaner background image. Additionally, to further enhance local information for improved detail rendition, we introduce a Local Model Residual Block, which integrates two local model blocks along with a s

Author

Li, Xiangyu; Fan, Wanshu; Shen, Yue; Wang, Cong; Wang, Wei; Yang, Xin; Zhang, Qiang; Zhou, Dongsheng

Published

2025

Language

EN