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Multi-focus image fusion based on probability filtering and region correction

机译:基于概率滤波和区域校正的多焦点图像融合

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Multi-focus image fusion is a common approach for extending the limited depth of field of cameras. However, existing focus measures cannot accurately identify focused pixels in multi-focus image fusion. It leads to the loss of focused pixels and the introduction of defocused pixels in the fused image. To solve this problem, a novel pixel-based fusion algorithm is proposed. In this algorithm, misidentified pixels are classified into two types: the dispersed and the clustered. Probability filtering and region correction are proposed to correct the dispersed and the clustered misidentified pixels, respectively. Experimental results show that the misidentified pixels are corrected by probability filtering and region correction, and the fusion algorithm is superior to the conventional algorithms and the state-of-the-art algorithms in terms of both subjective evaluation and objective evaluation. (C) 2018 Elsevier B.V. All rights reserved.
机译:多焦点图像融合是扩展摄像机有限景深的常用方法。然而,现有的聚焦措施不能准确地识别多聚焦图像融合中的聚焦像素。这导致聚焦像素的丢失以及融合图像中散焦像素的引入。为了解决这个问题,提出了一种新的基于像素的融合算法。在该算法中,误识别的像素分为两种类型:分散的和聚类的。提出了概率滤波和区域校正的方法,分别校正分散的和聚集的误识别像素。实验结果表明,通过概率滤波和区域校正对误识别的像素进行了校正,在主观评价和客观评价方面,融合算法均优于传统算法和最新算法。 (C)2018 Elsevier B.V.保留所有权利。

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