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A NEW REAL-WORLD HAZY IMAGE DATASET FOR IMAGE ENHANCEMENT AND RECOGNITION


Article Information

Title: A NEW REAL-WORLD HAZY IMAGE DATASET FOR IMAGE ENHANCEMENT AND RECOGNITION

Authors: Sanaullah Memon, Rafaqat Hussain Arain, Ghulam Ali Mallah, Sagar Lohana, Farheen Mirza

Journal: Spectrum of Engineering Sciences

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31

Publisher: Sociology Educational Nexus Research Institute

Country: Pakistan

Year: 2025

Volume: 3

Issue: 3

Language: en

Keywords: Computer VisionReal-world datasetImage dehazingMachine learningImage enhancementImage recognition

Categories

Abstract

Many computer vision tasks are benefited significantly from deep learning. However, research in the field of single image dehazing is still needed. The unclear image boundaries and dense haze degrade the visible quality of haze-free images. For measuring the efficiency of techniques, many deep learning-based approaches are evaluated on the real-world hazy image datasets for more credibility. Moreover, this study discusses on creation of a dataset that includes real-world hazy images. The dataset is valuable for computer vision and image processing research. It offers training resource for deep neural networks and machine learning models to handle more hazy circumstances.


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