SOFTWARE DEVELOPMENT FOR IMAGE PROCESSING: NOISE REDUCTION METHODS

This paper examines modern methods for reducing noise in digital images, as well as the capabilities of the OpenCV library for this type of image processing. The main types of noise affecting image quality and their suppression methods, such as median filters, wavelet transform, Gaussian blur, and nearest-neighbor filtering, are analyzed. Each method is examined in detail, including its mathematical model and its implementation in the OpenCV library.

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Publication Details

Published
2025-06-15
DOI
https://doi.org/10.21667/978-5-7722-0426-9-43-47
Primary Topic
Image and Signal Denoising Methods
Type
article
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article

SOFTWARE DEVELOPMENT FOR IMAGE PROCESSING: NOISE REDUCTION METHODS

S.V. Kroshilina, V.S. Tulyukov
Image and Signal Denoising Methods
article

SOFTWARE DEVELOPMENT FOR IMAGE PROCESSING: NOISE REDUCTION METHODS

S.V. Kroshilina, V.S. Tulyukov
article en

Abstract

This paper examines modern methods for reducing noise in digital images, as well as the capabilities of the OpenCV library for this type of image processing. The main types of noise affecting image quality and their suppression methods, such as median filters, wavelet transform, Gaussian blur, and nearest-neighbor filtering, are analyzed. Each method is examined in detail, including its mathematical model and its implementation in the OpenCV library.

Openalex Percentile: Top 78%
Image and Signal Denoising Methods
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SOFTWARE DEVELOPMENT FOR IMAGE PROCESSING: NOISE REDUCTION METHODS — S.V. Kroshilina, V.S. Tulyukov · (2025) | TGRS Research Map | TGRS