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首页> 外文期刊>Journal of Applied Remote Sensing >Saliency-based visualization of hyperspectral satellite images using hierarchical fusion
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Saliency-based visualization of hyperspectral satellite images using hierarchical fusion

机译:基于显着的高光谱卫星图像使用层次融合的可视化

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摘要

Owing to a large number of spectral bands, it is always a challenge to devise an optimal visualization method for hyperspectral images. An algorithm must maintain a balance between dimensionality reduction and restoration of maximum spectral information. A methodology for visualization of hyperspectral imagery is proposed based on extraction of salient regions. For that, spectral bands are selected from different combinations of principal component analysis, minimum noise fraction, and saliency maps. A hierarchical fusion method is proposed, which is applied on the selected bands to obtain a final three band RGB image. The qualitative and quantitative results of the proposed method are very encouraging once compared with other state-of-the-art methods. (C) 2018 Society of Photo Optical Instrumentation Engineers (SPIE)
机译:由于大量光谱频带,设计了对高光谱图像的最佳可视化方法始终是一个挑战。 算法必须维持维度减少和恢复最大光谱信息之间的平衡。 提出了一种基于突出区域的提取来可视化高光谱图像的方法。 为此,频谱频带选自主成分分析,最小噪声分数和显着图的不同组合。 提出了一种分层融合方法,其应用于所选择的频带以获得最终的三个带RGB图像。 与其他最先进的方法相比,该方法的定性和定量结果非常令人鼓舞。 (c)2018年照片光学仪表工程师(SPIE)

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