HazeRD: An outdoor scene dataset and benchmark for single image dehazing

In this paper, a new dataset, HazeRD, is proposed for benchmarking dehazing algorithms under more realistic haze conditions. HazeRD contains fifteen real outdoor scenes, for each of which five different weather conditions are simulated. As opposed to prior datasets that made use of synthetically gen...

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Bibliographic Details
Published in2017 IEEE International Conference on Image Processing (ICIP) pp. 3205 - 3209
Main Authors Zhang, Yanfu, Ding, Li, Sharma, Gaurav
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Atmospheric modeling
benchmark
Benchmark testing
Cameras
dataset
dehazing
depth
Image color analysis
Meteorology
Scattering
Visualization
Online AccessGet full text
ISSN2381-8549
DOI10.1109/ICIP.2017.8296874

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Summary:In this paper, a new dataset, HazeRD, is proposed for benchmarking dehazing algorithms under more realistic haze conditions. HazeRD contains fifteen real outdoor scenes, for each of which five different weather conditions are simulated. As opposed to prior datasets that made use of synthetically generated images or indoor images with unrealistic parameters for haze simulation, our outdoor dataset allows for more realistic simulation of haze with parameters that are physically realistic and justified by scattering theory. All images are of high resolution, typically six to eight megapixels. We test the performance of several state-of-the-art dehazing techniques on HazeRD. The results exhibit a significant difference among algorithms across the different datasets, reiterating the need for more realistic datasets such as ours and for more careful benchmarking of the methods.
ISSN:2381-8549
DOI:10.1109/ICIP.2017.8296874