Raindrop In-Situ Captured Benchmark Image Dataset and Evaluation
When taking photos through glass windows in rainy days,the raindrops adhered to glass surfaces are usually presented in the images,which not only degrade the visibility of the image but also prevent many computer vision algorithms from functio-ning properly.The research on raindrop removal is a scientific research to remove raindrops from such rainy images.The single-image raindrop removal research presents significant challenges due to the diverse and unique forms of raindrops found in nature.The varying transparency of raindrops further complicates the task of removing raindrop artifacts and degrades the imaging quali-ty of background scenes,adversely impacting the performance of existing raindrop removal algorithms.To facilitate a comprehen-sive understanding of this research area,this paper provides a detailed introduction to single-image raindrop removal,covering two main aspects:single-image raindrop removal algorithms and joint raindrop removal algorithms for single images.Additionally,a summary and evaluation of existing algorithms in this field are presented.However,the performance of the algorithm is often li-mited by the quality and quantity of the dataset in deep learning based methods,but in existing raindrop datasets,common situa-tions such as low-quality raindrop images and insufficient image quantities exist.In existing raindrop datasets,there are common situations such as poor quality of raindrop images and insufficient number of raindrop images.This paper proposes a higher edu-cation megacenter(HEMC)dataset.Camera shake,window reflections and other external disturbances are avoided as much as possible thus improving the image quality of the training set and accuracy of the test set and indirectly improving the performance of the raindrop removal methods.HEMC is evaluated in various aspects using competent visual effects and objective metrics.Ex-perimental results show the diversity of the raindrop images in HEMC and stability of the objective metrics.In addition,the re-sults verify the universality and stability of the HEMC in the raindrop removal methods.
NETL
NSTL
万方数据
