Presentation + Paper
7 June 2024 Color image denoising: a hybrid approach for mixed Gaussian and impulsive noise
Bogdan Smolka, Damian Kusnik, Milena Smolka, Michal Kawulok, Boguslaw Cyganek
Author Affiliations +
Abstract
This paper tackles the problem of mixed Gaussian and impulsive noise suppression in color images. The proposed method comprises two essential steps. Firstly, we detect impulsive noise through an approach based on the concept of digital path exploring the local pixel neighborhood. Each pixel is assigned a cost of a path connecting the boundary of a local processing window with its center. When the central pixel exhibits a high value of the path with lowest cost, it is identified as an impulse. To achieve this, we use a thresholding procedure for detecting corrupted pixels. Analyzing the distribution of minimum path costs, we employ the k-means technique to classify pixels into three distinct categories: those nearly undistorted, those corrupted by Gaussian noise, and those affected by impulsive noise. Subsequently, we employ the Laplace interpolation technique to restore the impulsive pixels — a fast and effective method yielding satisfactory denoising results. In the second step, we address the residual Gaussian noise using the Non-Local Means method, which selectively considers pixels from the local window that have not been flagged as impulsive. The experimental results confirm that our proposed hybrid method consistently yields superior outcomes compared to state-of-the-art denoising techniques. Moreover, its computational complexity remains low, rendering it suitable for real-time applications.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Bogdan Smolka, Damian Kusnik, Milena Smolka, Michal Kawulok, and Boguslaw Cyganek "Color image denoising: a hybrid approach for mixed Gaussian and impulsive noise", Proc. SPIE 13034, Real-Time Image Processing and Deep Learning 2024, 1303405 (7 June 2024); https://doi.org/10.1117/12.3013424
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KEYWORDS
Denoising

Digital filtering

Image filtering

Distortion

Image processing

Interpolation

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