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Detection of local motion blurred/non-blurred regions in an image

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Abstract

Motion blur of an image is a common phenomenon that occurs while taking a photograph due to the relative movement of the object and an image acquiring device. It is essential to detect this phenomenon of blurring of images in many applications such as information retrieval. This paper proposes a novel local blur detection technique, and it performs better than the existing works. This technique mainly uses Radon transform and Laplacian of Gaussian on the local neighborhood around each pixel to estimate blur information. Additionally, two new weight functions are introduced based on local geodesic distance and local variance. It is shown that these functions play a significant role in segregating blur and non-blurred parts. Simulation results validate the correctness and accuracy by testing the proposed algorithm on some challenging images with similar color information in the foreground and background. Various quantitative performance measures have determined the superiority of the proposed method.

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Data Availability

The data set used in this paper is available with the corresponding author upon a reasonable request.

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Acknowledgements

The authors would like to thank the Defence Institute of Advanced Technology, Pune, and Centre for Airborne Systems, Bangalore, for providing infrastructure for research work.

Funding

This study received no specific grant from any funding agency in the public, commercial, or non profit sectors.

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Authors and Affiliations

  1. Centre for Airborne Systems (CABS), Bangalore, 560037, India

    B R Kapuriya

  2. School of Computer Engineering and Mathematical Sciences, Defence Institute of Advanced Technology (DIAT), Pune, 411025, India

    Debasish Pradhan

  3. Aeronautics Research and Development Board (ARDB), DRDO, Delhi, 110054, India

    Reena Sharma

Authors
  1. B R Kapuriya
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  2. Debasish Pradhan
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  3. Reena Sharma
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Correspondence to Debasish Pradhan.

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Kapuriya, B.R., Pradhan, D. & Sharma, R. Detection of local motion blurred/non-blurred regions in an image. Multimed Tools Appl 83, 43705–43725 (2024). https://doi.org/10.1007/s11042-023-17340-3

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  • DOI: https://doi.org/10.1007/s11042-023-17340-3

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