Single Image Deraining : From Model-Based to Data-Driven and Beyond

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

130 Scopus Citations
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  • Wenhan Yang
  • Robby T. Tan
  • Shiqi Wang
  • Yuming Fang
  • Jiaying Liu

Related Research Unit(s)


Original languageEnglish
Pages (from-to)4059-4077
Journal / PublicationIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number11
Online published19 May 2020
Publication statusPublished - Nov 2021


The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation. The early single-image deraining methods employ a cost function, where various priors are developed to represent the properties of rain and background layers. Since 2017, single-image deraining methods step into a deep-learning era, and exploit various types of networks, i.e., convolutional neural networks, recurrent neural networks, generative adversarial networks, etc., demonstrating impressive performance. Given the current rapid development, in this paper, we provide a comprehensive survey of deraining methods over the last decade. We summarize the rain appearance models, and discuss two categories of deraining approaches: model-based and data-driven approaches. For the former, we organize the literature based on their basic models and priors. For the latter, we discuss the developed ideas related to architectures, constraints, loss functions, and training datasets. We present milestones of single-image deraining methods, review a broad selection of previous works in different categories, and provide insights on the historical development route from the model-based to data-driven methods. We also summarize performance comparisons quantitatively and qualitatively. Beyond discussing the technicality of deraining methods, we also discuss the future possible directions.

Research Area(s)

  • Rain, Atmospheric modeling, Videos, Image coding, Visualization, Degradation, Machine learning, Rain streak removal, single image, model-based, data-driven, QUALITY ASSESSMENT, RAIN, REMOVAL, CONTEXT, NETWORK, SPARSE

Citation Format(s)

Single Image Deraining: From Model-Based to Data-Driven and Beyond. / Yang, Wenhan; Tan, Robby T.; Wang, Shiqi et al.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 11, 11.2021, p. 4059-4077.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review