- Preprocessing experiments and applicators for EyeSea.
- Numerically optimized matrix computation implementation of image enhancement and color restoration algorithms.
- Callable image enhancement and restoration APIs.
- 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
.
- To only generate the images:
- The processed images are stored in the corresponding
data/output/
directory.
- 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.
- 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.