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Image registration optimization mechanism based on reinforcement learning and real time denoising

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Abstract

Image noise has a serious impact on image transmission, image data collection and image processing. Image noise is mainly denoised by additive noise and multiplicative noise. Firstly, based on the analysis that random noise has a direct impact on image recognition accuracy and registration performance, aiming at capturing and controlling the interaction between reinforcement learning agents and noise environment, an image recognition model based on noise stimulation is proposed, which will help capture and analyze random noise. Then, in order to construct a complete image data set and its linear combination of transfer process, a denoising algorithm based on reinforcement learning is proposed, which uses the sparse vector based on noise obtained by reinforcement learning to represent a given noise signal. Finally, based on image denoising based on reinforcement learning, an image registration optimization mechanism is proposed by maximizing the similarity measure between two images or minimizing the distance measure to find the coordinate correspondence between images. The simulation results show that the proposed algorithm is credible, effective and efficient in terms of consistency of noise analysis, accuracy of correspondence between feature points, registration error and computational utility of the algorithm.

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Acknowledgements

The authors would like to thank the support from Fujian Provincial Education Department Funds Science and Technology Projects (NO. 2017 JAT170321).

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Authors and Affiliations

  1. College of Mechanical and Energy Engineering, Jimei University, Xiamen, 361021, Fujian, China

    Jiangyan Ke

  2. School of Electrical Engineering, University of Jinan, Jinan, 250022, China

    Zhijie Zhang

  3. Huazhong Agricultural University, Wuhan, 430070, Hubei, China

    Ye Yingze

Authors
  1. Jiangyan Ke
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  2. Zhijie Zhang
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  3. Ye Yingze
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Correspondence to Jiangyan Ke.

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Ke, J., Zhang, Z. & Yingze, Y. Image registration optimization mechanism based on reinforcement learning and real time denoising. Multimed Tools Appl 79, 9489–9508 (2020). https://doi.org/10.1007/s11042-019-07914-5

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  • DOI: https://doi.org/10.1007/s11042-019-07914-5

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