Custom Filter-based Enhancement of MRI Images for Impulse Noise

This paper introduces a novel approach for enhancing MRI images corrupted by impulse noise. Impulse noise often degrades image quality, especially in medical imaging applications where accurate representation is critical. The proposed method employs a custom filter to remove impulse noise while maintaining essential image features. The custom filter is designed by altering the average value of its surrounding pixels depending on whether the pixel is entirely black or completely white. The filter’s design is determined by the specifications of MRI images and noise patterns typically encountered in such data. The proposed custom filter exhibits the effective operation of the denoising technique and fully utilizes the benefits of the improved median filter in eliminating impulse noise. The results demonstrate an improvement in image quality based on various quality metrics. There is a 6% improvement in Peak Signal Noise Ratio, 0.5% in Mean Square Error, 1% in Structural Similarity Index Measure, 0.7% in Image Quality and 0.3% in Average Gradient compared to a conventional median filter. Experimental results demonstrate significant improvements in image quality and preservation of diagnostic information compared to existing methods. The proposed approach offers a promising solution for enhancing MRI images affected by impulse noise, thereby aiding in more accurate diagnosis and treatment planning in medical imaging.

Authors

Institutions

Publication Details

Journal
Communications in Mathematics and Applications
Published
2024-11-30
DOI
https://doi.org/10.26713/cma.v15i3.2692
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Custom Filter-based Enhancement of MRI Images for Impulse Noise

Varsha Bendre, Kalpana Patil
Communications in Mathematics and Applications
Image and Signal Denoising Methods
article

Custom Filter-based Enhancement of MRI Images for Impulse Noise

Varsha Bendre, Kalpana Patil
article en

Abstract

This paper introduces a novel approach for enhancing MRI images corrupted by impulse noise. Impulse noise often degrades image quality, especially in medical imaging applications where accurate representation is critical. The proposed method employs a custom filter to remove impulse noise while maintaining essential image features. The custom filter is designed by altering the average value of its surrounding pixels depending on whether the pixel is entirely black or completely white. The filter’s design is determined by the specifications of MRI images and noise patterns typically encountered in such data. The proposed custom filter exhibits the effective operation of the denoising technique and fully utilizes the benefits of the improved median filter in eliminating impulse noise. The results demonstrate an improvement in image quality based on various quality metrics. There is a 6% improvement in Peak Signal Noise Ratio, 0.5% in Mean Square Error, 1% in Structural Similarity Index Measure, 0.7% in Image Quality and 0.3% in Average Gradient compared to a conventional median filter. Experimental results demonstrate significant improvements in image quality and preservation of diagnostic information compared to existing methods. The proposed approach offers a promising solution for enhancing MRI images affected by impulse noise, thereby aiding in more accurate diagnosis and treatment planning in medical imaging.

Communications in Mathematics and ApplicationsVol. 15(3)
Savitribai Phule Pune University (IN)
Affordable and clean energy
Openalex Percentile: Top 70%
Image and Signal Denoising Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Custom Filter-based Enhancement of MRI Images for Impulse Noise — Varsha Bendre, Kalpana Patil · Communications in Mathematics and Applications (2024) | TGRS Research Map | TGRS