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<p>Enhancing underwater images is essential for marine biology, underwater archaeology, and surveillance applications. However, images captured beneath the surface often present challenges like low contrast, poor visibility, color distortion, and noise, complicating their analysis and interpretation. This work introduces a practical approach to improving underwater imagery to overcome these obstacles. Noise and artifacts are removed using pre-processing techniques. The Discrete Wavelet Transform (DWT) divides the image into sub-bands, allowing for multiscale analysis. A novel color balancing algorithm is introduced to restore natural hues, counteracting the color changes resulting from water absorption and scattering. While Adaptive Laplace Enhancement (ALE) sharpens edges and details in images, Contrast Limited Adaptive Histogram Equalization (CLAHE) increases contrast. Quantitative metrics such as the Underwater Image Quality Measure (UIQM), Peak Signal-to-Noise Ratio (PSNR), and Underwater Color Image Quality Evaluation (UCIQE) are used to evaluate the efficacy of the suggested approach. When compared to current techniques for improving underwater photos, experimental results show notable gains in image quality and perceptual fidelity.</p>

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An adaptive Laplace enhancement method for underwater image dehazing

  • 期刊论文

  • 发表日期：

    2025年10月8日

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  • Kalyani Kapula,
  • Srinivas Thirumala,
  • M. Srilatha,
  • Anuragh Vijjapu,
  • A. Sravanthi Peddinti

摘要

Enhancing underwater images is essential for marine biology, underwater archaeology, and surveillance applications. However, images captured beneath the surface often present challenges like low contrast, poor visibility, color distortion, and noise, complicating their analysis and interpretation. This work introduces a practical approach to improving underwater imagery to overcome these obstacles. Noise and artifacts are removed using pre-processing techniques. The Discrete Wavelet Transform (DWT) divides the image into sub-bands, allowing for multiscale analysis. A novel color balancing algorithm is introduced to restore natural hues, counteracting the color changes resulting from water absorption and scattering. While Adaptive Laplace Enhancement (ALE) sharpens edges and details in images, Contrast Limited Adaptive Histogram Equalization (CLAHE) increases contrast. Quantitative metrics such as the Underwater Image Quality Measure (UIQM), Peak Signal-to-Noise Ratio (PSNR), and Underwater Color Image Quality Evaluation (UCIQE) are used to evaluate the efficacy of the suggested approach. When compared to current techniques for improving underwater photos, experimental results show notable gains in image quality and perceptual fidelity.