TSNet:A Two-stage Network for Image Dehazing with Multi-scale Fusion and Adaptive Learning

arXiv:2404.02460v1 Announce Type: new
Abstract: Image dehazing has been a popular topic of research for a long time. Previous deep learning-based image dehazing methods have failed to achieve satisfactory dehazing effects on both synthetic datasets and real-world datasets, exhibiting poor generalization. Moreover, single-stage networks often result in many regions with artifacts and color distortion in output images. To address these issues, this paper proposes a two-stage image dehazing network called TSNet, mainly consisting of the multi-scale fusion module (MSFM) and …

abstract arxiv cs.ai cs.cv datasets deep learning effects fusion image network networks popular research scale stage synthetic type world