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EXPOSURE FUSION BY FAST AND ADAPTIVE BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION

机译:快速和自适应二维经验模态分解的曝光融合

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摘要

A new method for fusing a scene of two or more differentrnexposed images is proposed. The process of Fast andrnAdaptive Bidimensional Empirical mode Decompositionrnis adopted in order to decompose the illuminationrncomponent of the input images in their Intrinsic ModernFunctions (IMFs). The features of each image can then berndetected by applying local energy operators within thernIMFs and the final fused image is derived as a collectionrnof features from the input images. Finally, the colorrninformation is selected from the “best exposed” pixels ofrnthe input sequence. Experimental results show that thisrnmethod captures all the features from the input imagesrnwhile the fused images display uniform pixel values in thernentire image region.
机译:提出了一种融合两个或更多不同曝光图像场景的新方法。为了对输入图像的固有现代函数(IMF)进行分解,采用了快速且自适应的二维经验模式分解过程。然后,可以通过在IMF中应用局部能量算子来检测每个图像的特征,并从输入图像中将最终融合图像作为集合特征导出。最后,从输入序列的“最佳曝光”像素中选择颜色信息。实验结果表明,该方法从输入图像中捕获了所有特征,而融合图像在整个图像区域中显示出均匀的像素值。

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