Fusion of Multifocus Images by Combining Edge Maps and the Sum-Modified-Laplacian Technique

Zijun Feng, Xiaoling Zhang, Huijie Zhang
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引用次数: 2

Abstract

Image fusion refers to an image processing technique that produces a single image with more information by combining the images of the same scene. The different focus images involve different details according to changing the lens of camera. In this paper, we propose an efficient method formulti focus image fusion by choosing focus regions based on decision map that reflects the clarity of an image. In order to obtain the high pass details of an image, a difference coefficients map between an isotropic diffusion model and Gaussian filter is presented. Sum-Modified-Laplacian (SML)improves the robustness of process by selecting high pass coefficients. Experimental results demonstrate the proposed fusion algorithm exhibits better performance than some compared methods, both in visual effect and objective evaluation criteria.
结合边缘映射和和修正拉普拉斯技术的多聚焦图像融合
图像融合是指将同一场景的图像组合在一起,产生具有更多信息的单一图像的图像处理技术。随着相机镜头的变化,不同焦距的图像涉及到不同的细节。本文提出了一种有效的焦点图像融合方法,即基于反映图像清晰度的决策图选择焦点区域。为了获得图像的高通细节,提出了各向同性扩散模型与高斯滤波器之间的差系数映射。和修正拉普拉斯算子(SML)通过选择高通系数来提高过程的鲁棒性。实验结果表明,所提出的融合算法在视觉效果和客观评价标准上都优于一些比较方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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