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Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation

Otsu's algorithm is one of the most well-known methods for automatic image thresholding. 2D Otsu's method is more robust compared to 1D Otsu's method. However, it still has limitations on salt-and-pepper noise corrupted images and uneven illumination images. To alleviate these limitat...

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Autores principales: Xing, Jiangwa, Yang, Pei, Qingge, Letu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439172/
https://www.ncbi.nlm.nih.gov/pubmed/32849864
http://dx.doi.org/10.1155/2020/5047976
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author Xing, Jiangwa
Yang, Pei
Qingge, Letu
author_facet Xing, Jiangwa
Yang, Pei
Qingge, Letu
author_sort Xing, Jiangwa
collection PubMed
description Otsu's algorithm is one of the most well-known methods for automatic image thresholding. 2D Otsu's method is more robust compared to 1D Otsu's method. However, it still has limitations on salt-and-pepper noise corrupted images and uneven illumination images. To alleviate these limitations and improve the overall performance, here we propose an improved 2D Otsu's algorithm to increase the robustness to salt-and-pepper noise together with an adaptive energy based image partition technology for uneven illumination image segmentation. Based on the partition method, two schemes for automatic thresholding are adopted to find the best segmentation result. Experiments are conducted on both synthetic and real world uneven illumination images as well as real world regular illumination cell images. Original 2D Otsu's method, MAOTSU_2D, and two latest 1D Otsu's methods (Cao's method and DVE) are included for comparisons. Both qualitative and quantitative evaluations are introduced to verify the effectiveness of the proposed method. Results show that the proposed method is more robust to salt-and-pepper noise and acquires better segmentation results on uneven illumination images in general without compromising its performance on regular illumination images. For a test group of seven real world uneven illumination images, the proposed method could lower the ME value by 15% and increase the DSC value by 10%.
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spelling pubmed-74391722020-08-25 Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation Xing, Jiangwa Yang, Pei Qingge, Letu Comput Intell Neurosci Research Article Otsu's algorithm is one of the most well-known methods for automatic image thresholding. 2D Otsu's method is more robust compared to 1D Otsu's method. However, it still has limitations on salt-and-pepper noise corrupted images and uneven illumination images. To alleviate these limitations and improve the overall performance, here we propose an improved 2D Otsu's algorithm to increase the robustness to salt-and-pepper noise together with an adaptive energy based image partition technology for uneven illumination image segmentation. Based on the partition method, two schemes for automatic thresholding are adopted to find the best segmentation result. Experiments are conducted on both synthetic and real world uneven illumination images as well as real world regular illumination cell images. Original 2D Otsu's method, MAOTSU_2D, and two latest 1D Otsu's methods (Cao's method and DVE) are included for comparisons. Both qualitative and quantitative evaluations are introduced to verify the effectiveness of the proposed method. Results show that the proposed method is more robust to salt-and-pepper noise and acquires better segmentation results on uneven illumination images in general without compromising its performance on regular illumination images. For a test group of seven real world uneven illumination images, the proposed method could lower the ME value by 15% and increase the DSC value by 10%. Hindawi 2020-08-11 /pmc/articles/PMC7439172/ /pubmed/32849864 http://dx.doi.org/10.1155/2020/5047976 Text en Copyright © 2020 Jiangwa Xing et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Xing, Jiangwa
Yang, Pei
Qingge, Letu
Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
title Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
title_full Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
title_fullStr Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
title_full_unstemmed Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
title_short Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
title_sort robust 2d otsu's algorithm for uneven illumination image segmentation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439172/
https://www.ncbi.nlm.nih.gov/pubmed/32849864
http://dx.doi.org/10.1155/2020/5047976
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