Performance Comparison of Different Digital and Analog Filters Used for Biomedical Signal and Image Processing

Document Type : Research Paper

Authors

1 Department of Computer Science and Engineering, S.A. Engineering College (Autonomous), Chennai, Tamil Nadu, India.

2 Global Institute of Engineering and Technology, Tamilnadu, Ranipet, India.

3 Department of Computer Science and Engineering, SRKR Engineering College Bhimavaram, Chinamiram Rural, Andhra Pradesh, India.

4 Associate Professor, Research Supervisor/School of EEE at Sathyabama Institute of Science & Technology, Chennai, Tamilnadu, India.

5 Principal, C. Abdul Hakeem College of Engineering & Technology, Melvisharam-632509, Ranipet District, Tamil Nadu, India.

10.22059/jitm.2024.96379

Abstract

Getting highly accurate output in biomedical data processing concerning biomedical signals and images is impossible because biomedical data are generated from various electronic and electrical resources that can deliver the data with noise. Filtering is widely used for signal and image processing applications in medical, multimedia, communications, biomedical electronics, and computer vision. The biggest problem in biomedical signal and image processing is developing a perfect filter for the system. Digital filters are more advanced in precision and stability than analog filters. Digital filters are getting more attention due to the increasing advancements in digital technologies. Hence, most medical image and signal processing techniques use digital filters for preprocessing tasks. This paper briefly explains various filters used in medical image and signal processing. Matlab is a famous mathematical, analytical software with a platform and built-in tools to design filters and experiment with different inputs. Even though this paper implements filters like, Mean, Median, Weighted Average, Guassian, and Bilateral in Python to verify their performance, a suitable filter can be selected for biomedical applications by comparing their performance.

Keywords

References

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Journal of Information Technology Management
Volume 16, Issue 1
2024
Pages 135-148

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