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Enhancing scene perception using a multispectral fusion of visible–near-infrared image pair

机译:使用可见-近红外图像对的多光谱融合来增强场景感知

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摘要

In this study, a method for fusing of visible (or standard RGB) with near-infrared (NIR) image pair for enhancing a hazy image is proposed. Better image enhancement in terms of contrast, sharpness, increased perception is realised by combining the components from both the spectra. While there are a number of applications that use NIR images, very few combine RGB and NIR information of the same scene taken from two separate imaging devices. Although NIR images are greyscaled in nature, they have intrinsic properties desirable in both colour and visible imagery of a number of scenes. Instances are increased the contrast between sky and clouds; shadowed and non-shadowed regions; and increased optical depth. These features are in most cases missed by a standard RGB camera and therefore, a fusion of such RGB-NIR image pairs is highly beneficial. The scheme for fusing these image pairs is realised by using a novel, fuzzy clustering algorithm along with wavelet transform so that not only contrast and sharpness are enhanced, but also the chromaticity of the original RGB image is retained. The proposed technique is well demonstrated for various outdoor scenes, and better results are obtained when compared against some of the state-of-the-art techniques proposed recently.
机译:在这项研究中,提出了一种将可见光(或标准RGB)与近红外(NIR)图像对融合以增强模糊图像的方法。通过结合两个光谱的成分,可以在对比度,清晰度,增强的感知度方面实现更好的图像增强。尽管有许多使用NIR图像的应用程序,但很少有结合使用从两个单独的成像设备获取的同一场景的RGB和NIR信息的应用程序。尽管NIR图像本质上是灰度的,但它们具有在许多场景的彩色图像和可见图像中都需要的固有属性。实例增加了天空和云彩之间的对比度;阴影和非阴影区域;并增加了光学深度。在大多数情况下,标准RGB相机会忽略这些功能,因此,将此类RGB-NIR图像对进行融合非常有益。通过使用新颖的模糊聚类算法以及小波变换来实现融合这些图像对的方案,从而不仅增强了对比度和清晰度,而且还保留了原始RGB图像的色度。与各种最近提出的最新技术相比,所提出的技术已在各种室外场景中得到了充分证明,并且获得了更好的结果。

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