Benchmarking Single Image Dehazing and Beyond [article]

Boyi Li and Wenqi Ren and Dengpan Fu and Dacheng Tao and Dan Feng and Wenjun Zeng and Zhangyang Wang
2019 arXiv   pre-print
We present a comprehensive study and evaluation of existing single image dehazing algorithms, using a new large-scale benchmark consisting of both synthetic and real-world hazy images, called REalistic Single Image DEhazing (RESIDE). RESIDE highlights diverse data sources and image contents, and is divided into five subsets, each serving different training or evaluation purposes. We further provide a rich variety of criteria for dehazing algorithm evaluation, ranging from full-reference
more » ... to no-reference metrics, to subjective evaluation and the novel task-driven evaluation. Experiments on RESIDE shed light on the comparisons and limitations of state-of-the-art dehazing algorithms, and suggest promising future directions.
arXiv:1712.04143v4 fatcat:ncgis7lbufdbrme6a3wsknq65m