• Neelofer sideeq
• Vikas Kumar

Light scattering and color change are two major sources of distortion for underwater photography. Light scattering is caused by the incidence of light on objects reflected and deflected multiple times by particles present in the water before reaching the camera. This in turn lowers the visibility and contrast of the image captured. Color change corresponds to the varying degrees of attenuation encountered by light traveling in the water with different wavelengths, rendering ambient underwater environments dominated by a bluish tone. No existing underwater processing techniques can handle light scattering and color change distortions suffered by underwater images, and the possible presence of artificial lighting simultaneously. This thesis proposes a novel systematic approach to enhance underwater images by a dehazing algorithm. The novel idea proposed in this method is to use color transfer to transform images into the same color space in order to reduce lighting in homogeneities which optimize grasshopper optimization after that threshold which come from optimization used by total variation and enhance the underwater image. The analysis of the proposed model by PSNR and MSE parameters is done and is compared with existing approaches.

Digital image processing, Contrast limited adaptive histogram equalization, Bilateral Filtering.

"UNDER WATER IMAGE ENHANCEMENT USING HYBRID INTELLIGENT OPTIMIZATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.170-177, June 2019, Available :http://www.jetir.org/papers/JETIR1906N75.pdf

"UNDER WATER IMAGE ENHANCEMENT USING HYBRID INTELLIGENT OPTIMIZATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp170-177, June 2019, Available at : http://www.jetir.org/papers/JETIR1906N75.pdf