README.md

metadata

license: cc-by-4.0
language:
  - en
tags:
  - image
  - dehazing
  - dehazer
  - classification
  - haze
  - hazy
  - hazespace2m
  - removal
  - enhancement
  - restoration
  - image restoration
  - image enhancement
  - single image dehazing
  - multi weather dehazing
  - dehazing dataset
pretty_name: >-
  Single Image Dehazing Dataset with Over 2 Million Hazy Images of three
  different types of hazes such as fog, cloud, and environmental haze (EH) of 10
  different intense levels.
size_categories:
  - 100B<n<1T
task_categories:
  - image-classification
task_ids:
  - multi-class-image-classification

Published in ACM Multimedia 2024, Melbourne, Australia

HazeSpace2M: A Dataset for Haze Aware Single Image Dehazing [Paper]

Md Tanvir Islam ¹, Nasir Rahim ¹, Saeed Anwar ², Muhammad Saqib ³, Sambit Bakshi ⁴, Khan Muhammad ^{1, *}

| 1. Sungkyunkwan University, South Korea | 2. KFUPM, KSA | 3. UTS, Australia | 4. NIT Rourkela, India || *Corresponding Author |

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IMPORTANT UPDATES

• 2025/03/22 | Fixed the indexing issues of the Farmland subset.
• 2025/03/21 | Identified an indexing issue between GT and Haze images. We are working on it to fix the issues.

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Dataset Description

GitHub Repository: https://github.com/tanvirnwu/HazeSpace2M

Paper: https://dl.acm.org/doi/abs/10.1145/3664647.3681382

Point of Contact: [email protected]

Dataset Size: Outdoor: 269GB | Street: 295GB | Farmland: 90GB | Satellite: 153GB

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HazeSpace2M Dataset

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HazeSpace2M Folder Structure

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Proposed Multi-stage Haze Aware Dehazing

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Cite This Paper

If you find our work useful in your research, please consider citing our paper:

@inproceedings{hazespace2m,
  title={HazeSpace2M: A Dataset for Haze Aware Single Image Dehazing},
  author={Islam, Md Tanvir and Rahim, Nasir and Anwar, Saeed and Saqib Muhammad and Bakshi, Sambit and Muhammad, Khan},
  booktitle={Proceedings of the 32nd ACM International Conference on Multimedia},
  year={2024},
  doi = {10.1145/3664647.3681382}
}