Jul 23, 2023 · Artificial Intelligence

Ten Deep Learning Based Image Dehazing Algorithms: Principles, Implementations, and Comparisons

This article reviews ten state‑of‑the‑art single‑image dehazing methods—including DehazeNet, MSCNN, AOD‑Net, NLD, SSLD, EPDN, DAD, PSD, MSBDN and GFN—detailing their underlying atmospheric scattering models, network architectures, training pipelines, advantages, drawbacks, and providing links to papers, code repositories and illustrative results.

AICNNImage Processing

0 likes · 28 min read

Ten Deep Learning Based Image Dehazing Algorithms: Principles, Implementations, and Comparisons

DataFunTalk

Jun 30, 2022 · Artificial Intelligence

Self‑Augmented Unpaired Image Dehazing via Density and Depth Decomposition (D4)

The paper introduces D4, a self‑augmented unpaired image dehazing framework that decomposes the transmission map into fog density and scene depth, enabling realistic fog synthesis for data augmentation and achieving superior dehazing performance with fewer parameters and FLOPs on multiple benchmarks.

CVPR2022Computer VisionDepth estimation

0 likes · 14 min read

Self‑Augmented Unpaired Image Dehazing via Density and Depth Decomposition (D4)