Underwater image restoration and enhancement using a Hybrid algorithm to evaluate the undersea activities like underwater vehicles to carry optical imaging systems for recording. The captured images and videos frequently suffered from two displeasing problems: 1. Color distortion; 2. Poor visibility. Those factors are the most notorious threats in underwater imaging systems because the light is exponentially attenuated while penetrating through water and the strength of attenuation is color dependent. Under these inferences, an effective single underwater image restoration, and enhancement framework-based Sea-thru algorithm has been proposed for image restoration, depth estimation, and transmission compensation to enhance the image. To address the consequences of scattering and absorption, a new restoration algorithm outperformed by the state-of-the-art method both qualitatively and quantitatively. A wide variety of underwater images with various scenarios were exploited to assess the restoration performance of the proposed algorithm. The proposed underwater image restoration technique is a promising result for undersea activities that required high-quality images. Sea-thru method estimates backscatter using the dark pixels and machine learning algorithms, to create exciting opportunities for future underwater image exploration and conservation