基于相关系数的DCT域多焦点图像融合

M. A. Naji, A. Aghagolzadeh
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引用次数: 22

摘要

多焦点图像融合用于从不同聚焦深度的输入图像中收集有用和必要的信息,以创建理想的包含所有输入图像信息的输出图像。本文提出了一种基于离散余弦变换(DCT)域相关系数计算的高效、简便的多焦点图像融合方法。基于DCT的图像融合算法是一种非常合适的图像融合算法,特别是在视觉传感器网络(VSN)中使用JPEG图像时,它节省了大量的时间和精力。该方法对输入的多焦点图像经过低通滤波后的变化量进行评估,然后选择变化较大的块。为了评估算法的性能,使用了大量编码为JPEG的对多聚焦图像。结果表明,该方法的输出图像质量优于以往的方法。
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Multi-focus image fusion in DCT domain based on correlation coefficient
Multi-focus image fusion is used to collect useful and necessary information from input images with different focus depths in order to create an output image that ideally has all information from input images. In this article, an efficient, new and simple method is proposed for multi-focus image fusion which is based on correlation coefficient calculation in the discrete cosine transform (DCT) domain. Image fusion algorithms which are based on DCT are very appropriate, and they consume less time and energy, especially when JPEG images are used in visual sensor networks (VSN). The proposed method evaluates the amount of changes of the input multi-focus images when they pass through a low pass filter, and then selects the block which has been changed more. In order to assess the algorithm performance, a lot of pair multi-focused images which are coded as JPEG were used. The results show that the output image quality is better than that of the previous methods.
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