Application of Different Techniques for Underwater Image Processing- A Systematic Review

Abstract

The area of underwater image processing has gained huge attention among the researchers because of its wide application. Image processing is the approach of developing the input image quality so that it would be understood easily by users in future. Image processing develops the data content of image and changes the images visual impact on the observer. Image processing intensifies the image features and accentuates the features of image like corners, contrast to enhance the photographs display which is much helpful for study and examination. Several methods and techniques have been used by researchers worldwide in order to resolve the underwater image processing issues. This paper reviews different techniques of underwater image processing and also compares the techniques among each other. This paper discusses about the filtering method, histogram-based equalization method and particle swarm optimization techniques and compares them with their advantages.

Image segmentation-based optimization algorithms: A Review

“…MRI brain image has many regions like Gray matter, White matter, CSF, skull etc. An efficient segmentation of brain regions must be done which make clinicians, to provide the appropriate treatment [52,53,54]. The MRI brain images are chosen from brain web database.…”

“…Obtaining the objects visibility at short or long distance in underwater scenes is very challenging and a difficult task. The atmospheric light is the main hurdle to process the UW images from bad conditions of visibility under the water, light attenuation, and light scattering due to entire reasons which the UW images faces a lot and influence their contrast and visibility which they comprise originally [57,58,59,60].…”