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Sadhana

, Volume 41, Issue 2, pp 225–238 | Cite as

Real-time underwater image enhancement: An improved approach for imaging with AUV-150

  • JEET BANERJEE
  • RANJIT RAY
  • SIVA RAM KRISHNA VADALI
  • SANKAR NATH SHOME
  • SAMBHUNATH NANDY
Article

Abstract

An RGB YCbCr Processing method (RYPro) is proposed for underwater images commonly suffering from low contrast and poor color quality. The degradation in image quality may be attributed to absorption and backscattering of light by suspended underwater particles. Moreover, as the depth increases, different colors are absorbed by the surrounding medium depending on the wavelengths. In particular, blue/green color is dominant in the underwater ambience which is known as color cast. For further processing of the image, enhancement remains an essential preprocessing operation. Color equalization is a widely adopted approach for underwater image enhancement. Traditional methods normally involve blind color equalization for enhancing the image under test. In the present work, processing sequence of the proposed method includes noise removal using linear and non-linear filters followed by adaptive contrast correction in the RGB and YCbCr color planes. Performance of the proposed method is evaluated and compared with three golden methods, namely, Gray World (GW), White Patch (WP), Adobe Photoshop Equalization (APE) and a recently developed method entitled “Unsupervised Color Correction Method (UCM)”. In view of its simplicity and computational ease, the proposed method is recommended for real-time applications. Suitability of the proposed method is validated by real-time implementation during the testing of the Autonomous Underwater Vehicle (AUV-150) developed indigenously by CSIR-CMERI.

Keywords

Underwater image enhancement anisotropic diffusion color cast CLAHE linear and non-linear filters. 

Notes

Acknowledgements

The authors would like to thank CSIR and to the Ministry of Earth Sciences, Govt of India for providing financial assistance to carry out the work . The authors wish to express sincere thanks to all Robotics & Automation Group members for their help and support. We are thankful to Dr. Rajlaxmi Chouhan of Computer Vision Laboratory, Dept. of E & ECE, Indian Institute of Technology, Kharagpur for her valuable insights in preparing the manuscript.

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Copyright information

© Indian Academy of Sciences 2016

Authors and Affiliations

  • JEET BANERJEE
    • 1
  • RANJIT RAY
    • 2
  • SIVA RAM KRISHNA VADALI
    • 2
  • SANKAR NATH SHOME
    • 2
  • SAMBHUNATH NANDY
    • 2
  1. 1.School of MechatronicsCSIR-Central Mechanical Engineering Research InstituteDurgapurIndia
  2. 2.Robotics and Automation DivisionCSIR-Central Mechanical Engineering Research InstituteDurgapurIndia

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