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

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Amini Rad R.; Afifi A.; Fahimifar M. H.

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Journal Paper

Paper Information

Journal: JOURNAL OF ELECTRONIC AND CYBER DEFENCE Year:2021 | Volume:9 | Issue:4 Page(s): 77-86

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Information Journal Paper

Title

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

Author(s)

Amini Rad R. | Afifi A. | Fahimifar M. H. | Issue Writer Certificate

Keywords

Passive Millimeter Wave Imaging

Image Fusion

Bidimensional Empirical Mode Decomposition

Shearlet Transform

ISCM Neural Network Fusion Evaluation Criterion

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.

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