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Detection of images degraded by rain using image quality assessment

  • 1204: Multimedia Technology for Security and Surveillance in Degraded Vision
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Abstract

Various weather conditions degrade images, and hence the quality of the images is compromised to a large extent. Atmospheric conditions like Rain, Fog, Haze, Mist, etc., degrade scenes, and the scene’s acquisition results in noisy images. The noisy images have less visibility than regular images. Therefore, the images degraded by the weather conditions need some special attention before processing them. Otherwise, the processing of noisy images using the same process applied for noise-free images cannot find the desired results. Hence, the identification of images degraded by weather conditions is essential before further processing. Rain is one of the most complex atmospheric conditions that degraded images. In the case of rain, water droplets present in the air are visible, wherein,in other atmospheric conditions, water droplets cannot be seen. In rainy images, the large size of water droplets in the air causes more complex degradation. This research paper has proposed a technique for detecting images degraded by rain using an image quality assessment approach. We have used no-reference image quality assessment techniques for this work. We have proposed an image quality metric specially designed for the images degraded by rain. We have used the proposed metric along with other state-of-the-art metrics for identifying rainy images. Our proposed technique has been evaluated using a public dataset containing about 1500 images. We found promising results by applying our technique to that dataset to detect images degraded by rain. This technique can help security and surveillance applications, where the automatic selection of degraded frames is crucial.

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Data availability

Public Dataset used, Available online:https://engineering.jhu.edu/vpatel36/datasets/

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Acknowledgments

The first author is grateful to the DRDO, GoI, for providing Junior Research Fellowship (JRF) (Letter No. ERIP/ER/DG-Med & CoS/990116507/M/01/1716. The authors are thankful forthe Indo-Austrian joint project grant No. INT/AUSTRIA/BMWF/P-25/2018 funded by the DST, GOI, and the SPARC project (ID: 231) funded by MHRD, GOI. This work was also supported in part by the project of Grant Agency of Excellence, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, 188, Raja S. C. Maulik Road, Kolkata, 700032, India

    Ratnadeep Dey & Debotosh Bhattacharjee

  2. Center for Basic and Applied Science, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 500 03, Hradec Kralove, Czech Republic

    Debotosh Bhattacharjee & Ondrej Krejcar

  3. Malaysia-Japan International Institute of Technology (MJIIT), UniversitiTeknologi Malaysia, Jalan Sultan Yahya Petra, 54100, Kuala Lumpur, Malaysia

    Ondrej Krejcar

Authors
  1. Ratnadeep Dey
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  2. Debotosh Bhattacharjee
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  3. Ondrej Krejcar
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Contributions

(i) Novel Technique to detect images degraded by Rain using Image Quality Assessment (ii) Novel no-reference image quality metric for analysis of the quality of Rainy images.

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Correspondence to Ratnadeep Dey.

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Dey, R., Bhattacharjee, D. & Krejcar, O. Detection of images degraded by rain using image quality assessment. Multimed Tools Appl 81, 35445–35461 (2022). https://doi.org/10.1007/s11042-022-13041-5

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  • DOI: https://doi.org/10.1007/s11042-022-13041-5

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