This survey paper has provided clear and detailed information about the degradation of the underwater images and enhancement techniques for improving the image quality. It describes the overall insight on the restoration techniques using neural networks and physical based methods. The datasets and subjective tasks required for the filtering of the underwater images are also covered.

1. Filtering underwater image
Survey on Underwater image filtering: methods, datasets and evaluation
Chau Yi Li Riccardo Mazzon Andrea Cavallaro
Presented by Rishitha Bandi

3. What causes underwater image degradation?
• Attenuation of light
• The depth of the objects from the surface
• the distance between the camera and objects
• composition of water are a few of the factors

4. What can we see upon image degradation?
• Colour cast
• Blurring

5. Restoration of underwater images
• improve the known degradation operations on the degraded image.
• Physical based models are used for the restoration.
• Image prior is a convolutional neural network used for enhancing the
image without any prior training data.
• Neural networks are initialized randomly and used as training data to
solve inverse problems such as noise reduction, super-resolution, and
inpainting.
• Prior is used for estimating the background light and transmission
map, which determines how the image is degraded

6. Restoration methods
• DCP observes that the minimum intensity across the three colour channels
is usually close to zero in an haze-free image, whereas in an hazy image it is
increasingly shifted towards that of the haze color
• Haze Line prior uses the overall distribution of the RGB intensities
• UDCP discards the most degraded red colour channel and states that
objects closer to the camera, with less degraded colours, have low
intensities in either of the blue or green channels
• ARC directly exploits the loss in red intensity and the increase in blue and
green intensity along with the range.
• CB proposed to consider the difference between the red color channel and
the less attenuated blue and green color channels.

7. Ehancement
• Enhancement is the process of improving the quality of the image to
look better.
• It changes the colors, contrasts, or improves the performance of
computer vision algorithms.

8. Purpose of enhancement methods
• enhancement methods are used in the color spaces like CIELab and
HSL
• White balancing handles color dependent degradation
• White balancing algorithms algorithms operate in RGB or CIELab color
spaces

9. Learning based methods
• Target images is the main challenge in learning based models
• Generative Adversarial Network frameworks are used for supervised
learning models
• CycleGAN is used for weakly supervised learning based models
• CycleGAN has one GAN for selecting target image and second GAN
for degrading image after filtering

10. Datasets
• Natural datasets which are degraded by the water medium.
• Degradation of the water images due to the chemicals added to the
water or digitally.

11. Subjective Tasks
Comparison of restoration and enhancement on both coastal and
oceanic water images filtering.
Restoration Tasks
ARC(Automatic Red Channel)
DBL(Depth- compensated Background Light Restoration )
WCID(Wavelength Compensation Image Dehazing)
UWHL( Underwater Haze-line)
UWCNN(Underwater convolutional neural network)

12. Enhancement tasks
Fusion(Colour Balance and Fusion by Ancuti et al)., FUnIE, and
waterNET

14. Conclusion
• This survey paper has provided clear and detailed information about
the degradation of the underwater images and enhancement
techniques for improving the image quality. It describes the overall
insight on the restoration techniques using neural networks and
physical based methods. The datasets and subjective tasks required
for the filtering of the underwater images are also covered.

15. References
• https://arxiv.org/pdf/2012.12258.pdf
• https://puiqe.eecs.qmul.ac.uk/Demo
• https://blogs.mathworks.com/headlines/2020/01/20/computer-
vision-algorithm-removes-the-water-from-underwater-images/
• Restoration and Enhancement of Underwater Images Based on
Bright Channel Prior
This paper proposed a new method of underwater images restoration
and enhancement which was inspired by the dark…www.hindawi.com
• https://www.deryaakkaynak.com/research