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Research on Multi-focus Image Fusion Algorithm Based on Quadtree

机译:基于四叉树的多焦点图像融合算法研究

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摘要

Most of the multi-focus fusion algorithms currently are prone to image blur and loss of detail information. This paper proposes a multi-focus fusion algorithm based on quadtree decomposition which can almost overcome the above shortcomings. The research on multi-focus fusion algorithm based on quadtree decomposition is to divide the original image into several image sub-blocks and check regional consistency for each block to obtain the optimal block of the source image, and then detect the focus area for each block to obtain the initial fused decision image. Finally, the fused decision image is subjected to perform morphological processing to obtain a final fused image. Through extensive experiments on different source images, we show that the proposed method has better adaptability.
机译:当前,大多数多焦点融合算法都容易出现图像模糊和细节信息丢失的情况。提出了一种基于四叉树分解的多焦点融合算法,几乎可以克服上述缺点。基于四叉树分解的多焦点融合算法的研究是将原始图像划分为多个图像子块,并检查每个块的区域一致性,以获得源图像的最佳块,然后检测每个块的聚焦区域获得初始融合决策图像。最后,对融合决策图像进行形态学处理以获得最终融合图像。通过对不同源图像的大量实验,我们表明该方法具有更好的适应性。

著录项

  • 来源
    《》|2018年|457-464|共8页
  • 会议地点 Melbourne(AU)
  • 作者单位

    Hunan University, Chagnsha 410082, China;

    Hunan University, Chagnsha 410082, China;

    Hunan University, Chagnsha 410082, China;

    Hunan University, Chagnsha 410082, China;

    Hunan University, Chagnsha 410082, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Quadtree; Optimal block; Regional consistency;

    机译:四叉树;最佳区块区域一致性;

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