Investigating Different Filter Analyses for Underwater Image Enhancement Using Global Equalization

Underwater photography usually leads to significant blurriness and contrast decreases because of light absorption and scattering, This will restrict the utilization of important image data. In this research, suggest a technique,that addresses that kind of problem. This work consists of two stages, such as pixel intensity centre regionalization and global histogram equalization. The image is computed using a pixel intensity center localization approach based on various color models such as RGB, HSV, and YCbCr also uses various filters, in particular the Gaussian filter, bilateral filter, guided filter, top-hat filtering, bottom-hat filtering, top-bottom hat filtering, TopBottom hat filtering, Box filter, mean filter, Wiener filter. The histogram’s global equalization is used to adapt the image color based on the attributes of each channel. The proposed compression strategy can provide bright images without adding over-enhancement or additional computational effort. Comparison of quality and quantity results indicates the advantages of the various filters and color modes for underwater images.