Medical Image Denoisy Based on Machine Learning

Nankar Rani Laxman , Jadhav Dipali Bhausaheb , Deshmukh Bhagyshri Vijay , Deshmukh Arati Ravindra

Underwater Image, Image Enhancement, Transfer Learning, Light Scattering.

Image Enhancement is an important step in underwater research. The basic intent of image enhancing is to convert a blur image into a crystal clear image for the underwater research. So This paper discusses the technique for improving underwater image enhancement, these underwater images usually suffers from motion blur effect due to turbulence in the flow of water and non – uniform illumination and limited contrast. Due to the presence of distortion, captured underwater image needs to be processed in different ways. Underwater images captured in deep low light environment, are of worst quality and these images are low contrast, cause blurring effect, low contrast, scattering, absorption, noise color variation, clarity of image is reduced, quality get degrades and these underwater images cannot be directly used for various scientific research, marine biology research, underwater vehicles, submarine operations. While capturing underwater images some major obstacles are there such as minerals, salt, sand, planktons. These particles produce haziness in deep underwater captured image. To beat this, transfer learning base of Features model is taken on in this paper.

Published Paper   E-Certificate

"Medical Image Denoisy Based on Machine Learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.95 - 98, March-2023, Available :https://ijsdr.org/papers/IJSDR2303020.pdf

Volume 8 Issue 3, March-2023

Pages : 95 - 98

Paper Reg. ID: IJSDR_204368

Published Paper Id: IJSDR2303020

Downloads: 000347651

Research Area: Engineering

Country: -, -, --

Published Paper PDF: https://ijsdr.org/papers/IJSDR2303020

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2303020

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition