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Preprocessing for EyeSea

  • Preprocessing experiments and applicators for EyeSea.
  • Numerically optimized matrix computation implementation of image enhancement and color restoration algorithms.
  • Callable image enhancement and restoration APIs.

Procedure to Execute

  • Place the input images in data/input/ directory of the corresponding processing operation (i.e Color Restoration or Enhancement).
  • Edit the corresponding run.py script to uncomment the algorithm to be applied.
  • Execute the script:
    • To only generate the images: python run.py.
    • To visualize before-after stages for each image: python run.py --visualize.
  • The processed images are stored in the corresponding data/output/ directory.

Image Enhancement Algorithms

  • CLAHE: Contrast limited adaptive histogram equalization.
  • GC: Gamma Correction.
  • HE: Image enhancement by histogram transformation.
  • ICM: Underwater Image Enhancement Using an Integrated Colour Model.
  • Rayleigh Distribution: Underwater image quality enhancement through composition of dual-intensity images and Rayleigh-stretching.
  • RGHS: Shallow-Water Image Enhancement Using Relative Global Histogram Stretching Based on Adaptive Parameter Acquisition.
  • UCM: Enhancing the low quality images using Unsupervised Colour Correction Method.
  • UMASK: Unsharp Masking.
  • BF: Bilateral Filtering.

Image Color Restoration Algorithms

  • DCP: Single Image Dehazing using Dark Channel Prior.
  • GB Dehazing R Correction: Single underwater image restoration by blue-green channels dehazing and red channel correction.
  • IBLA: Underwater Image Restoration Based on Image Blurriness and Light Absorption.
  • LowComplexityDCP: Low Complexity Underwater Image Enhancement Based on Dark Channel Prior.
  • MIP: Initial results in underwater single image dehazing.
  • New Optical Model: Single underwater image enhancement with a new optical model (paper).
  • RoWS: Removal of water scattering.
  • UDCP: Transmission Estimation in Underwater Single Images.
  • ULAP: A Rapid Scene Depth Estimation Model Based on Underwater Light Attenuation Prior for Underwater Image Restoration.