articleJun 1, 2019Closed access

Enhanced Pix2pix Dehazing Network

Xiamen University · Horizon Robotics (China) · +1 more institution

Indexed incrossref

Abstract

In this paper, we reduce the image dehazing problem to an image-to-image translation problem, and propose Enhanced Pix2pix Dehazing Network (EPDN), which generates a haze-free image without relying on the physical scattering model. EPDN is embedded by a generative adversarial network, which is followed by a well-designed enhancer. Inspired by visual perception global-first theory, the discriminator guides the generator to create a pseudo realistic image on a coarse scale, while the enhancer following the generator is required to produce a realistic dehazing image on the fine scale. The enhancer contains two enhancing blocks based on the receptive field model, which reinforces the dehazing effect in both color…

Citation impact

774
total citations
FWCI
38.48
Percentile
100%
References
33
Citations per year

Authors

4

Topics & keywords

Keywords
  • Discriminator
  • Computer science
  • Generator (circuit theory)
  • Image (mathematics)
  • Translation (biology)
  • Artificial intelligence
  • Image translation
  • Perception
UN Sustainable Development Goals
  • Reduced inequalities
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