UIPS: A Novel Image Resolution and Clarity Enhancement Scheme for Underwater Image Processing Scheme

The primary goal of this system is to enhance the quality and efficiency of the underwater optical image, which is influenced by forward and reverse diffraction, absorption coefficient of light and marine snow, among other factors. Additionally, the suggested system is expanded to improve its perception through the identification of underwater mineral items. This approach is intended to facilitate analysis and reduce the time required for classifying and identifying mining objects through the use of a random forest classifier. This methodology is primarily implemented by integrating mine classification approaches to object identification using a random forest classifier. Additionally, to enhance the amount of picture data collected in order to perform accurate underwater object detection utilizing depth-based analysis. Automatic-Detection-and-Classification (ADC) of Underwater Structures for Mines Hunt Systems has been proposed in conjunction with the Random Forest Classifier in order to achieve the highest accuracy in image quality improvements. The term image ‘Super-Resolution’ provides a hint to image quality enhancement and robust feature assesment of digital images, in which the logic is applied to the underwater streams to enhance the quality of it in clear manner. This system utilizes the underwater image to enhance the quality and this technology enables real-time integration and efficient analysis of items resembling mines. The overall integration of ADC and RF scheme is called as Underwater Image Processing Scheme (UIPS), in whichit provides an efficient image quality in outcomes and the resulting section of this paper provides a proper proof of that in clear manner.