We propose a dual channel prior used for identifying pixels that are unlikely to comply with the dark channel assumption, leading to erroneous depth estimates.

We propose a dual channel prior used for identifying pixels that are unlikely to comply with the dark channel assumption, leading to erroneous depth estimates.

Dive into the research topics of 'Combining semantic scene priors and haze removal for single image depth estimation'. Together they form a unique fingerprint.

Combining semantic scene priors and haze removal for single image depth estimation. Published in WACV, 2014. Share on.

Combining semantic scene priors and haze removal for single image depth estimation. Ke Wang, Enrique Dunn, Joseph Tighe, Jan-Michael Frahm. 2014, IEEE Winter ...

Combining this prior with a physical haze imaging model, we can easily recover high quality haze-free images. Experiments demonstrate that our method is very ...

Several dehazing algorithms have obtained depth information by considering multiple images of the same scene, 3D modelling or images in different polarizations ...

Aug 3, 2023 · A supervised learning technique, CNN extracts features depending on the network depth. The architecture of CNN is different from traditional ...

Mar 2, 2024 · This framework integrates depth estimation and dehazing by a dual-task interaction mechanism and achieves mutual enhancement of their performance.

A novel semantic attention and relative scene depth-guided network (SARSDN) for underwater image enhancement is proposed.