Enhanced Pix2pix Dehazing Network
Xiamen University · Horizon Robotics (China) · +1 more institution
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
- FWCI
- 38.48
- Percentile
- 100%
- References
- 33
Authors
4Topics & keywords
- Discriminator
- Computer science
- Generator (circuit theory)
- Image (mathematics)
- Translation (biology)
- Artificial intelligence
- Image translation
- Perception
- Reduced inequalities