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Visible polarization image fusion with non-subsampled Shearlets

机译:非下采样Shearlets的可见偏振图像融合

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For the disadvantage of traditional target detection methods with low detection rate and difficulties in distinguishing the small temperature difference and camouflage targets, this paper presents a kind of visible polarization image fusion method using non-subsampled Shearlets transform. Firstly, we obtain four polarization status images by multi-detector camera, where the direction of polarization angle is 0° 、 45° 、 90° 、 135° separately. The Stokes vectors are calculated by polarization status images. Then, the extracted target polarization feature images and light intensity image are decomposed into several sub frequency bands by NSST with fine multi-scale decomposition characteristics. Meanwhile, the fusion coefficients are determined based on high-frequency energy window and low-frequency mean in the frequency domain. At last, the final fusion image is obtained after NSST inverse transform and target enhancement. Experimental results illustrate that the proposed approach could obtain better fusion images with rich details, high contrast, highlighting the polarization characteristic of the target to improve the ability of scene perception and target detection.
机译:针对传统目标检测方法检测率低,难以区分小温差和伪装目标的缺点,提出了一种基于非下采样Shearlets变换的可见光偏振图像融合方法。首先,通过多探测器相机获得四个偏振态图像,其中偏振角的方向分别为0°,45°,90°,135°。斯托克斯矢量是通过偏振状态图像计算的。然后,利用具有良好的多尺度分解特性的NSST将提取的目标偏振特征图像和光强度图像分解为几个子频带。同时,基于频域中的高频能量窗和低频均值来确定融合系数。最后,经过NSST逆变换和目标增强后,获得了最终的融合图像。实验结果表明,该方法可以获得更好的细节细节,高对比度融合图像,突出了目标的偏振特性,提高了场景感知和目标检测的能力。

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