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A Review of Remote Sensing Image Dehazing.

Juping Liu^1,2, Shiju Wang¹, Xin Wang¹

¹School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210000, China.

Sensors (Basel, Switzerland)

|July 2, 2021

Summary

Remote sensing (RS) data clarity is improved using advanced dehazing techniques. This study categorizes algorithms, discusses their pros and cons, and outlines future research for clearer Earth observation.

Keywords:

dark channel dehazenet image dehazing remote sensing image retinex

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Area of Science:

Earth and Space Sciences
Computer Science

Background:

Remote sensing (RS) data is crucial for Earth surface information.
Hazy conditions, especially in visible light bands, degrade RS data quality.
Existing methods aim to restore single hazy images without extra information.

Purpose of the Study:

To classify current remote sensing dehazing algorithms.
To summarize the advantages and disadvantages of each algorithm category.
To discuss evaluation metrics and application scenarios for RS data haze removal.

Main Methods:

Classification of dehazing algorithms into image enhancement, physical dehazing, and data-driven approaches.
Detailed summary of the pros and cons for each category.
Discussion of evaluation indicators and application scenarios.

Main Results:

Categorization of existing RS dehazing algorithms.
Analysis of the strengths and weaknesses of image enhancement, physical dehazing, and data-driven methods.
Identification of key evaluation metrics and application contexts.

Conclusions:

Current RS dehazing methods have limitations.
Further research is needed to address common deficiencies.
Future work should focus on improving haze removal techniques for better Earth observation.