Improving the Quality of Millimeter Wave Images by Fusion with Visible Images

Document Type : Original Article

Authors

1 M.Sc., Department of Electronics, Malek Ashtar University of Technology, Tehran, Iran

2 Associate Professor, Department of Electronics, Malek Ashtar University of Technology, Tehran, Iran

Abstract

Passive millimeter wave imaging is used to discover the objects concealed under a person's clothes. Discovering hidden objects is extremely important in the places such as airports, because of security. However, millimeter wave images have low-quality and image processing techniques are needed to improve the quality of the images. This paper attempts to use the fusion approach to present a method for discovering hidden objects from PMMW images while preserving the details of visible images. In the proposed method, images are subdivided using BEMD conversion into high frequency and low frequency sub-images.  In the next step, the NSST conversion is used to parse images from the previous step in different resolutions and directions, and then the improved SCM neural network is used as the fusion rule. The results are evaluated using fusion effectiveness criteria of QAB/F and MI. Simulation results show that the proposed method improves the previous results, which were combined using the NSST analysis method and the ISCM law, with an average of about 33% for the QAB/F criterion .

Keywords

References

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Electronic and Cyber Defense
Volume 9, Issue 4 - Serial Number 36
Serial No. 36, Winter Quarterly
February 2022
Pages 77-86

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History

  • Receive Date: 09 May 2021
  • Revise Date: 26 September 2021
  • Accept Date: 13 December 2021
  • Publish Date: 20 February 2022

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