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\(\gamma \) radiation image denoising method based on speckle splitting

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Abstract

For the problem of multiple noises in the visual images captured by CMOS sensors in the \(\gamma \) radiation environment, this paper proposed a two-stage image denoising method based on speckle splitting to improve the clarity of the \(\gamma \) radiation scene image. In the first stage, we first losslessly split the noisy image into multiple sub-images by dilated down-sampling, which makes the speckle noise of the original image decomposed into isolated point noise in the sub-images. And then, the isolated point noise is removed by detection-based median filtering. In the second stage, we present a gradient-guided NLM filtering in YUV color space, which further deals with the residual weak noise derived from the subtle difference between the non-salient speckle edge and background pixels. Extensive experiments are carried out on the practical scene images captured from Co60 \(\gamma \) radiation scene. With the help of our proposed scheme, the quality of noisy image has been obviously improved. Concretely, the PSNR is boosted by 8.17 dB and the SSIM is increased by 0.32. Experimental results demonstrate that the proposed method enjoys state-of-the-art performance in improving the clarity of \(\gamma \) radiation images.

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Acknowledgements

This work was supported by Sichuan Science and Technology Program (Grant No. 2021YFG0376/2021YFG0380). Thanks to Robot Technology Used for Special Environment Key Laboratory of Sichuan Province for providing the computing resources and analysis platform. Hao Deng also thanks his wife for the full support of this research.

Funding

This work was supported by Sichuan Science and Technology Program (Grant No. 2021YFG0376/2021YFG0380).

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Authors and Affiliations

  1. School of Information Engineering, Southwest University of Science and Technology, Qinglong Road, Mianyang, 621010, Sichuan, China

    Hao Deng, Hua Zhang & Hai Wang

  2. Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Qinglong Road, Mianyang, 621010, Sichuan, China

    Hao Deng, Hua Zhang, Hao Zhao & Hai Wang

  3. Department of Automation, University of Science and Technology of China, Huangshan Road, Hefei, 230026, Anhui, China

    Hao Zhao

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  1. Hao Deng
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  2. Hua Zhang
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Contributions

Hao Deng carried out the work related to \(\gamma \) radiation image acquisition, algorithm design and method implementation. Hao Zhao assisted in manuscript framework design and language revision. Prof. Hua Zhang provided full guidance on \(\gamma \) irradiation mechanism, data acquisition and mathematical methods. Hai Wang provided support in \(\gamma \) radiation image acquisition.

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Correspondence to Hua Zhang.

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Deng, H., Zhang, H., Zhao, H. et al. \(\gamma \) radiation image denoising method based on speckle splitting. SIViP 17, 1391–1399 (2023). https://doi.org/10.1007/s11760-022-02347-4

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  • DOI: https://doi.org/10.1007/s11760-022-02347-4

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