Open AccessUnderwater Image Enhancement with a Deep Residual Framework
Author(s) -
Anuja Phapale,
Puja Kasture,
Keshav Katkar,
Omkar Karale,
Atal Deshmukh
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst218428
Subject(s) - underwater , computer science , python (programming language) , correctness , residual , artificial intelligence , computer vision , image quality , feature (linguistics) , process (computing) , focus (optics) , image (mathematics) , algorithm , programming language , linguistics , oceanography , philosophy , geology , physics , optics
This paper focuses on framework developed with the goal to enhance the quality of underwater images using machine learning models for the Underwater Image enhancement system. It also covers the various technologies and language used in the development process using Python programming language.The developed system provides two major functionality such as feature to provide input as image or video and returns enhanced image or video depending upon user input type with focus on more image quality, sharpness, colour correctness etc.