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Multifocus color image sequence fusion based on mean shift segmentation

机译:基于均值漂移分割的多焦点彩色图像序列融合

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摘要

This paper presents a region-based technique for fusion of a multifocus color image sequence in the LUV color space. First, mean shift segmentation was applied on the weighted average image of the image sequence to obtain the fusion reference areas. Second, for each segmented area, the well-known modified Laplacian (LAP2) was used as a focus measure to select the clearest parts within the image sequence and then a final image focused with all parts can be generated. Mutual information, QAB/F metric, entropy, standard deviation, image sharpness metric, image contrast metric, average gradient, and spatial frequency were adopted to assess the quality of the fused image. Experiments carried out using standard image sequences from HeliconSoft demonstrated that the results obtained through our technique offer good performance. The proposed technique can be used to extend the depth of field (DOF) of a camera system effectively. (C) 2015 Optical Society of America
机译:本文提出了一种基于区域的技术,用于在LUV颜色空间中融合多焦点彩色图像序列。首先,对图像序列的加权平均图像应用均值偏移分割,以获得融合参考区域。其次,对于每个分割区域,使用众所周知的改良拉普拉斯算子(LAP2)作为聚焦度量,以选择图像序列中最清晰的部分,然后可以生成聚焦所有部分的最终图像。互信息,QAB / F度量,熵,标准偏差,图像清晰度度量,图像对比度度量,平均梯度和空间频率被用来评估融合图像的质量。使用HeliconSoft的标准图像序列进行的实验表明,通过我们的技术获得的结果具有良好的性能。所提出的技术可用于有效地扩展相机系统的景深(DOF)。 (C)2015年美国眼镜学会

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