Enhancing Image Quality for the Detection of Underwater Debris with Adaptive Fuzzy Filter

The image quality improvement process plays a very important role. This is because the process can increase the clarity and accuracy of image detection. One type of image detection that exists is the detection of garbage found under the sea. One of the image quality improvement processes is related to noise removal. Noise is a sudden increase in pixel intensity in an image. This can cause various problems that occur such as in medical photos, satellites, and photography. One method used to remove noise from images is using Adaptive Fuzzy Filter (AFF). This method is carried out by first finding the average value of the mean fuzzy set and the gray level fuzzy. After that, the value comparison process is carried out. From the results of the research conducted on 689 images from the dataset obtained, there is a decrease in the amount of noise of around 96,23% of the total noise obtained previously. This can certainly provide good results in terms of changes in noise that have been made.

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Publication Details

Journal
Indonesian Journal of Artificial Intelligence and Data Mining
Published
2025-02-17
DOI
https://doi.org/10.24014/ijaidm.v8i1.33010
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
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article

Enhancing Image Quality for the Detection of Underwater Debris with Adaptive Fuzzy Filter

Mustika Ulina, Apriyanto Halim, Frans Mikael Sinaga, Tanti Tanti
Indonesian Journal of Artificial Intelligence and Data Mining
Water Quality Monitoring Technologies
article

Enhancing Image Quality for the Detection of Underwater Debris with Adaptive Fuzzy Filter

Mustika Ulina, Apriyanto Halim, Frans Mikael Sinaga, Tanti Tanti
article en

Abstract

The image quality improvement process plays a very important role. This is because the process can increase the clarity and accuracy of image detection. One type of image detection that exists is the detection of garbage found under the sea. One of the image quality improvement processes is related to noise removal. Noise is a sudden increase in pixel intensity in an image. This can cause various problems that occur such as in medical photos, satellites, and photography. One method used to remove noise from images is using Adaptive Fuzzy Filter (AFF). This method is carried out by first finding the average value of the mean fuzzy set and the gray level fuzzy. After that, the value comparison process is carried out. From the results of the research conducted on 689 images from the dataset obtained, there is a decrease in the amount of noise of around 96,23% of the total noise obtained previously. This can certainly provide good results in terms of changes in noise that have been made.

Indonesian Journal of Artificial Intelligence and Data MiningVol. 8(1)
Openalex Percentile: Top 76%
Water Quality Monitoring Technologies
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