Abstract
Aiming at the fusion of visible and Passive Millimeter Wave (PMMW) images, a novel algorithm based on clustering and NSCT (Nonsubsampled Contourlet Transform) is proposed. It takes advantages of the particular ability of PMMW image in presenting metal target and uses the clustering algorithm for PMMW image to extract the potential target regions. In the process of fusion, NSCT is applied to both input images, and then the decomposition coefficients on different scale are combined using different rules. At last, the fusion image is obtained by taking the inverse NSCT of the fusion coefficients. Some methodologies are used to evaluate the fusion results. Experiments demonstrate the superiority of the proposed algorithm for metal target detection compared to wavelet transform and Laplace transform.
Highlights
A passive millimeter wave (PMMW) imaging system achieves images by detecting the difference of millimeter band energy that objects radiated, which has great performance in penetrating and excellence ability of recognizing a metal target from its surrounding environment [1]
The main difficulty in the PMMW imaging systems is low image quality due to wavelength, which cannot meet the demand of practical application
Considering the fact that even PMMW images with low pixel resolution still provide valuable information, it is deserved to combine it with a visible image to enhance the characteristic
Summary
A passive millimeter wave (PMMW) imaging system achieves images by detecting the difference of millimeter band energy that objects radiated, which has great performance in penetrating and excellence ability of recognizing a metal target from its surrounding environment [1]. Passive millimeter wave imaging system has large potential in the field of hidden objects detection because it is not harmful to humans [2]. Considering the fact that even PMMW images with low pixel resolution still provide valuable information, it is deserved to combine it with a visible image to enhance the characteristic. NSCT has the characteristic of shift-invariant; this paper presents the application of it for image fusion. An image pre-processing which specifics to PMMW image is adopted.
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