Qualitative evaluation of pixel level image fusion algorithms

M. Sumathi, R. Barani
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引用次数: 16

Abstract

Image fusion is the process of combining information from two or more images of a same scene into a single composite image that is more informative and is more suitable for visual perception or computer processing. The main objective of this paper is to implement the various pixel level fusion algorithms and to determine how well the information contained in the source images are represented in the fused images on multimodality and multifocusing images. Experiments and qualitative metrics dictate that Laplacian Pyramid method performs better on both multimodality and multifocusing images.
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像素级图像融合算法的定性评价
图像融合是将同一场景的两幅或多幅图像中的信息组合成信息量更大、更适合视觉感知或计算机处理的单个复合图像的过程。本文的主要目的是实现各种像素级融合算法,并确定在多模态和多聚焦图像上,源图像中包含的信息在融合图像中的表现程度。实验和定性指标表明,拉普拉斯金字塔方法在多模态和多聚焦图像上都有更好的表现。
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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