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Airborne Infrared and Visible Image Fusion for Target Perception Based on Target Region Segmentation and Discrete Wavelet Transform

机译:基于目标区域分割和离散小波变换的目标感知的空气传播红外和可见图像融合

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摘要

Infrared and visible image fusion is an important precondition of realizing target perception for unmanned aerial vehicles (UAVs), then UAV can perform various given missions. Information of texture and color in visible images are abundant, while target information in infrared images is more outstanding. The conventional fusion methods are mostly based on region segmentation; as a result, the fused image for target recognition could not be actually acquired. In this paper, a novel fusion method of airborne infrared and visible image based on target region segmentation and discrete wavelet transform (DWT) is proposed, which can gain more target information and preserve more background information. The fusion experiments are done on condition that the target is unmoving and observable both in visible and infrared images, targets are moving and observable both in visible and infrared images, and the target is observable only in an infrared image. Experimental results show that the proposed method can generate better fused image for airborne target perception.
机译:红外和可见的图像融合是实现无人机(无人机)的目标感知的重要前提,然后UAV可以执行各种特定任务。可见图像中纹理和颜色的信息丰富,而红外图像中的目标信息更加出色。传统的融合方法主要基于区域分割;结果,无法实际获取用于目标识别的融合图像。本文提出了一种基于目标区域分割和离散小波变换(DWT)的机载红外和可见图像的新型融合方法,其可以获得更多的目标信息并保持更多背景信息。融合实验在条件下完成,即目标在可见和红外图像中既不悬挂和观察,目标在可见和红外图像中都在移动和可观察,并且目标仅在红外图像中可观察到。实验结果表明,该方法可以为空降靶感知产生更好的融合图像。

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