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Journals / European Journal of Technique / 2019 / Cilt: 9 - Sayı: 2

A COMPARISON STUDY FOR IMAGE DENOISING

Muhammet Fatih ASLAN
Kadir SABANCI
Akif DURDU
Pages
145–150
Publication Date
2022-10-12
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Peak Signal-to-Noise Ratio, Mean Squared Error, Mean StructuralSimilarity and Feature Similarity Index are used as a comparison method.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Image denoising is the detection and removal of outliers in a image.
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Key Findings & Data:Both methods have been used toeliminate noise of different types and different rates added to the benchmarkand retina images.
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Conclusion & Impact:Peak Signal-to-Noise Ratio, Mean Squared Error, Mean StructuralSimilarity and Feature Similarity Index are used as a comparison method.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Image denoising is the detection and removal of outliers in a image. Ameasured analog signal is affected by both the device from which themeasurement is performed and the noise from the environment. Various typesof noise are available. With the developed noise reduction methods, it is triedto eliminate the existing noise. In this study, Bandelet Transform and BilateralFilter denoising methods are compared. Both methods have been used toeliminate noise of different types and different rates added to the benchmarkand retina images. Bandelet transform is performed for both hard and softthreshold. Peak Signal-to-Noise Ratio, Mean Squared Error, Mean StructuralSimilarity and Feature Similarity Index are used as a comparison method.

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Cite This Article

ASLAN, M. F., SABANCI, K., DURDU, A. (2022). A COMPARISON STUDY FOR IMAGE DENOISING. European Journal of Technique, Cilt: 9 - Sayı: 2, 145–150. https://ajindex.com/articles/512066

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