Impulse noise recuperation from grayscale and medical images using supervised curve fitting linear regression and mean filter
- Title
- Impulse noise recuperation from grayscale and medical images using supervised curve fitting linear regression and mean filter
- Creator
- Thomas S.; Krishna A.
- Description
- Acquisition of images from electronic devices or Transmission of the image through any medium will cause an additional commotion. This study aims to investigate a framework for eliminating impulse noise from grayscale and medical images by utilizing linear regression and a mean filter. Linear regression is a supervised machine learning algorithm that computes the value of a dependent variable based on an independent variable. The value of the recuperating pixel is measured using a curve-fitting, direction-based linear regression approach or applying a mean filter to the noise-free pixels. The efficiency of the proposed technique experiments with benchmark test images and the images of the USC-SIPI and TESTIMAGES data sets. Peak signal-to-noise ratio (PSNR) and structural similarity index metrics (SSIM) are determined to prove the performance of the proposed method. The results, when compared with the seven recent state-of-the-art techniques, show the superiority of the proposed method in terms of visual quality and accuracy. The proposed model achieves an average PSNR value of 65.21dB and an SSIM value of 0.999 for the reconstruction of medical images, proving its accuracy and efficiency. The impulse noise restoration process helps the radiologist get a clear visual clarity of the medical image for diagnosis purposes. 2022 Institute of Advanced Engineering and Science. All rights reserved.
- Source
- Indonesian Journal of Electrical Engineering and Computer Science, Vol-28, No. 2, pp. 777-786.
- Date
- 2022-01-01
- Publisher
- Institute of Advanced Engineering and Science
- Subject
- Image restoration; Interpolation; Machine learning; Noise removal; Rectilinear regression; Salt and pepper noise
- Coverage
- Thomas S., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, India, Department of Computer Science, Rajagiri College of Social Sciences, Mahatma Gandhi University, Kerala, India; Krishna A., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 25024752
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Thomas S.; Krishna A., “Impulse noise recuperation from grayscale and medical images using supervised curve fitting linear regression and mean filter,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/14825.