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Severe motion blurred silkworm pupae image restoration in sex discrimination

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Abstract

The task of sex determination of silkworm pupae is usually accomplished using machine learning technology. However, the captured image included much blur because of live silkworm pupae’s writhing, which makes sex discrimination more difficulty. Accordingly, the strategy to restore the blurred image is proposed in this paper. Firstly, effective sharp edges via rolling guidance filter are predicted. Then, in the kernel estimation step, \(L_{0}\) regularization term and the gradient prior are, respectively, to estimate the kernel and recover the intermediate latent image. Benefiting from the multi-scale computation scheme, the accurate kernel with continuity and sparsity is acquired. Finally, in the image restoration stage, a hyper-Laplacian prior is used to recover rich edges and textures in the clear image. Simulated and real tests were conducted to verify the availability of the proposed method. Furthermore, the proposed method can also be promoted to other challenging cases, including the large blur image and the image containing noises. All experiments prove the effectiveness of the proposed method.

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Funding

This research is supported by the National Natural Science Foundation of China under Grant No. 62265007, and Jiangxi Provincial Natural Science Foundation under Grant Nos. 20202BAB212007, 20202BABL214035, 20212BAB211009, and Jiangxi Provincial Science and Technology Project of Education Department under Grant Nos. GJJ200651, GJJ210644.

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Authors and Affiliations

  1. College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China

    Guangying Qiu & Dan Tao

  2. College of Engineering and Technology, Southwest University, Chongqing, 400715, China

    Qingying Li

  3. College of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, 430074, China

    Housheng Su

  4. Tobacco Leaf Branch of Chongqing Tobacco Corporation, Chongqing, 400000, China

    Chunlei Zhou

Authors
  1. Guangying Qiu
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  2. Qingying Li
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  3. Dan Tao
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  4. Housheng Su
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  5. Chunlei Zhou
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Contributions

GQ wrote the manuscript; DT revised the paper; HS revised the whole paper. CZ and QL revised the grammar errors.

Corresponding authors

Correspondence to Dan Tao or Housheng Su.

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Qiu, G., Li, Q., Tao, D. et al. Severe motion blurred silkworm pupae image restoration in sex discrimination. SIViP 17, 1985–1996 (2023). https://doi.org/10.1007/s11760-022-02411-z

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  • DOI: https://doi.org/10.1007/s11760-022-02411-z

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