@inproceedings{dd9085f4cdd64e33b95b00c1d6310d91,
title = "On the Application of Robust Mean Shift Procedure for the Enhancement of Noisy Color Images",
abstract = "Image corruption due to noise disturbances severely decreases color image quality and therefore image enhancement is a vital step of the processing pipeline. Our approach modifies the standard Mean-Shift technique, so that the algorithm is able to work directly on noisy color images and offers very satisfying denoising results. The proposed Robust Mean-Shift is resistant to the mixed Gaussian and impulsive noise and can be used in various practical imaging tasks. The described technique has been validated on a database containing a variety of color images contaminated with various noise intensity levels and the obtained results show that it significantly excels the classical Mean-Shift algorithm. Image noise is to large extent suppressed, edges are sharpened and details are retained which enables the improvement of the image segmentation process.",
keywords = "image denoising, impulsive noise, mean-shift, mixed noise, robust filter, segmentation",
author = "Damian Kusnik and Bogdan Smolka",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 10th IEEE Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems, ICCC 2022 ; Conference date: 06-07-2022 Through 09-07-2022",
year = "2022",
doi = "10.1109/ICCC202255925.2022.9922686",
language = "English",
series = "ICCC 2022 - IEEE 10th Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "23--28",
booktitle = "ICCC 2022 - IEEE 10th Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems, Proceedings",
address = "United States",
}