BFO-ICA based multi focus image fusion

S. Agrawal, S. Swain, Lingraj Dora
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引用次数: 5

Abstract

This paper presents a pixel based multi focus image fusion technique using independent component analysis (ICA) and bacteria foraging optimization (BFO) algorithm. The basic idea here is to obtain the ICA bases from a set of registered images and optimize them using BFO. The novelty in this paper is that BFO-ICA has not been applied to multi-focus image fusion. The images in the ICA domain are fused and the fused image is then reconstructed using inverse transform. The results are compared with FastICA and PSO-ICA. It is observed that optimizing with BFO yield better result.
基于BFO-ICA的多焦点图像融合
提出了一种基于独立分量分析(ICA)和细菌觅食优化(BFO)算法的像素多焦点图像融合技术。这里的基本思想是从一组配准图像中获得ICA基,并使用BFO对其进行优化。本文的新颖之处在于BFO-ICA尚未应用于多焦点图像融合。将ICA域中的图像进行融合,然后对融合后的图像进行逆变换重建。结果与FastICA和PSO-ICA进行了比较。结果表明,用BFO优化效果较好。
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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