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X-ray bio-image denoising using directional-weighted-mean filtering and block matching approach

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Abstract

An X-ray bio-image might suffer interference from salt-and-pepper (SAP) noise during transmission or capture, thus reducing image quality. This paper proposes a three-stage method to cope with this problem. A directional-weighted-mean (DWM) filter is used to remove the corruption noise in the first stage. In the second stage, extreme pixel (255 or 0 for an 8-bit gray level bio-image) confirmation is performed to restore the X-ray bio-images. In the final stage, block matching identifies blocks with similar textures in a local region. The center pixels of these similar blocks are then averaged to refine the gray value of the restored pixel, thus allowing improvement to the quality of the restored X-ray image through consideration of the texture properties in neighbor pixels over a large size window. Experimental results show that the proposed approach can effectively remove background noise from a SAP noise corrupted bio-image for various noise densities. The reconstructed bio-image does not incur blurring even under heavy noise corruption.

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Acknowledgements

The authors wish to thank the Ministry of Science and Technology of the Republic of China for financially supporting this research under Contract Grants nos. MOST 105-2410-H-025-015-MY2, MOST 104-2221-E-468-007 and MOST 106-2410-H-468-009. The authors also gratefully acknowledges the Editor and anonymous reviewers for their valuable comments and constructive suggestions.

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Authors and Affiliations

  1. Department of Information Communication, Asia University, Taichung, 41354, Taiwan, ROC

    Ching-Ta Lu, Jun-Hong Shen, Ling-Ling Wang & Chia-Hua Liu

  2. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40402, Taiwan, ROC

    Ching-Ta Lu & Jun-Hong Shen

  3. Department of Information Management, National Taichung University of Science and Technology, Taichung, 404, Taiwan, ROC

    Mu-Yen Chen

  4. School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu, Fukushima, 9658580, Japan

    Neil Y. Yen

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  1. Ching-Ta Lu
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  2. Mu-Yen Chen
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  3. Jun-Hong Shen
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  4. Ling-Ling Wang
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  6. Chia-Hua Liu
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Correspondence to Mu-Yen Chen.

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Lu, CT., Chen, MY., Shen, JH. et al. X-ray bio-image denoising using directional-weighted-mean filtering and block matching approach. J Ambient Intell Human Comput (2018). https://doi.org/10.1007/s12652-018-0692-8

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