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Sand Dust Images Enhancement Based on Red and Blue Channels.

Fei Shi1,2, Zhenhong Jia1,2, Huicheng Lai1,2

  • 1School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.

Sensors (Basel, Switzerland)
|March 10, 2022
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This study introduces a novel algorithm to enhance sandstorm images by correcting color casts and removing dust particles. The method significantly improves image quality in adverse weather conditions, outperforming existing techniques.

Keywords:
BDPRRCCimage enhancementred channelsand dust images

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Area of Science:

  • Computer Vision
  • Image Processing
  • Remote Sensing

Background:

  • Sandstorm degradation causes color casting, low contrast, and lost details, reducing image quality.
  • Traditional restoration methods struggle with persistent color casting and inaccurate atmospheric light estimation.

Purpose of the Study:

  • To develop an effective algorithm for sand dust image enhancement.
  • To correct color casting and improve visibility in sandstorm-affected images.

Main Methods:

  • Proposed a two-module algorithm: Red Channel-based Correction (RCC) for color casting and Blue Channel-based Dust Particle Removal (BDPR).
  • RCC module corrects color imbalances.
  • BDPR module removes sand dust particles.

Main Results:

  • The proposed algorithm effectively corrects color casting and removes dust particles.
  • Enhanced images exhibit improved clarity and visibility.
  • Qualitative and quantitative analyses confirm significant image quality improvements.

Conclusions:

  • The developed sand dust image enhancement algorithm significantly boosts image quality under sandstorm conditions.
  • The method outperforms state-of-the-art restoration algorithms in sandstorm image enhancement.