Image quality enhancement by applying a combination of filtering between the median filter and CLAHE

Digital image quality is often degraded due to disturbances such as salt-and-pepper noise and uneven lighting. This can hinder further image analysis and processing. This research aims to improve image quality by applying a combination of two filtering methods, namely Median Filter and CLAHE (Contrast Limited Adaptive Histogram Equalization), using MATLAB. Median Filter is used to remove impulsive noise without obscuring important details, while CLAHE is applied to improve image contrast adaptively and locally. Tests were conducted on grayscale images with artificial noise added. The experimental results show that the combination of both methods provides a significant improvement in image quality compared to the use of either method alone. Thus, this approach is effectively used for image pre-processing that requires detail recovery and contrast enhancement.

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Publication Details

Journal
Internet of Things and Artificial Intelligence Journal
Published
2025-05-31
DOI
https://doi.org/10.31763/iota.v5i2.921
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
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article

Image quality enhancement by applying a combination of filtering between the median filter and CLAHE

Lailan Sofinah Harahap, Adinda Tarisyah Hsb, Hasti Fadillah
Internet of Things and Artificial Intelligence Journal
Image and Signal Denoising Methods
article

Image quality enhancement by applying a combination of filtering between the median filter and CLAHE

Lailan Sofinah Harahap, Adinda Tarisyah Hsb, Hasti Fadillah
article en

Abstract

Digital image quality is often degraded due to disturbances such as salt-and-pepper noise and uneven lighting. This can hinder further image analysis and processing. This research aims to improve image quality by applying a combination of two filtering methods, namely Median Filter and CLAHE (Contrast Limited Adaptive Histogram Equalization), using MATLAB. Median Filter is used to remove impulsive noise without obscuring important details, while CLAHE is applied to improve image contrast adaptively and locally. Tests were conducted on grayscale images with artificial noise added. The experimental results show that the combination of both methods provides a significant improvement in image quality compared to the use of either method alone. Thus, this approach is effectively used for image pre-processing that requires detail recovery and contrast enhancement.

Internet of Things and Artificial Intelligence JournalVol. 5(2)
Universitas Islam Negeri Sumatera Utara (ID)
Openalex Percentile: Top 87%
Image and Signal Denoising Methods
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