Medical Image denosy base on Machine Learning

Authors: Dipali Bhausaheb Jadhav, Rani Laxman Nankar, Arati Ravindra Deshmukh, Bhagyashri Vijay Deshmukh, Dalvi A.S.

Country: India

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Abstract: Image Enhancement is an important step in Medical research. The basic intent of image enhancing is to convert a blur image into a crystal-clear image for the Medical research. Paper discusses the technique for improving Medical image enhancement, these Medical 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 Medical image needs to be processed in different ways. Medical 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 Medical images cannot be directly used for various scientific research, marine biology research, Medical vehicles, submarine operations. While capturing Medical images some major obstacles are there such as minerals, salt, sand, planktons. These particles produce haziness in deep Medical captured image. To beat this, transfer learning base of Features model is taken in this paper. [1]

Keywords: Medical Image, Image Enhancement, Transfer Learning, Light Scattering

Paper Id: 230177

Published On: 2023-05-27

Published In: Volume 11, Issue 3, May-June 2023

Cite This: Medical Image denosy base on Machine Learning - Dipali Bhausaheb Jadhav, Rani Laxman Nankar, Arati Ravindra Deshmukh, Bhagyashri Vijay Deshmukh, Dalvi A.S. - IJIRMPS Volume 11, Issue 3, May-June 2023.

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