Deep Learning Algorithms for Single Image Deraining

Three deep learning based algorithms are compared in terms of standard figures of merit and visual quality for single image deraining. The comparative analysis additionally considers several classic approaches based on redundant representations or Gaussian Mixture Models. Experimental results are reported for both synthetic and real images, revealing higher quality of the neural based approaches.