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An Improved Image Enhancing Technique for Underwater Images - A. Sai Suneel - Bog

An Improved Image Enhancing Technique for Underwater Imagesaf A. Sai Suneel
Bag om An Improved Image Enhancing Technique for Underwater Images

Recently a lot of study has been done on improving the visual quality of underwater and undersea imaging in submarine and military operations to find the hidden structure designs and sea excursions. This project proposed an underwater image enhancement method based on colour constancy theory. When we compare with much of the existing research, the time and complexity of the proposed method are low, and it achieves excellent performance. Firstly, we analyse the underwater imaging model and distortion. Then, by compensating the red channel and applying local white balance, a linear transformation is performed. Finally, results are obtained by applying the histogram equalization to the RGB images. We also measure the image quality by taking the parameters PSNR, UIQM, UCIQE and Entropy. These parameters are compared to proposed and existing approaches; however, our method produces higher image quality.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9786206739838
  • Indbinding:
  • Paperback
  • Sideantal:
  • 52
  • Udgivet:
  • 11. juli 2023
  • Størrelse:
  • 150x4x220 mm.
  • Vægt:
  • 96 g.
  • 2-3 uger.
  • 19. december 2024
På lager
Forlænget returret til d. 31. januar 2025

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Beskrivelse af An Improved Image Enhancing Technique for Underwater Images

Recently a lot of study has been done on improving the visual quality of underwater and undersea imaging in submarine and military operations to find the hidden structure designs and sea excursions. This project proposed an underwater image enhancement method based on colour constancy theory. When we compare with much of the existing research, the time and complexity of the proposed method are low, and it achieves excellent performance. Firstly, we analyse the underwater imaging model and distortion. Then, by compensating the red channel and applying local white balance, a linear transformation is performed. Finally, results are obtained by applying the histogram equalization to the RGB images. We also measure the image quality by taking the parameters PSNR, UIQM, UCIQE and Entropy. These parameters are compared to proposed and existing approaches; however, our method produces higher image quality.

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