一种基于多向梯度滤波的异构图像融合方法

Zhilong Ren, K. Du, Chenghu Mou, Yi Liang
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引用次数: 0

摘要

针对传统异构图像融合方法存在特征缺失、边缘模糊、易受噪声干扰和灰度过渡不平滑等问题,提出了一种基于多向梯度滤波的异构图像融合方法。该方法利用拉普拉斯金字塔的多尺度和梯度滤波的多方向提取源图像的细节,防止灰度过渡不平滑;引入自适应模糊耦合机制,解决了源图像特征容易丢失的问题;梯度显著性映射策略避免了边缘模糊和噪声干扰。实验结果表明,该方法可以实现异构图像的有效融合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Heterogeneous Image Fusion Method Based on Multi-directional Gradient Filtering
Aiming at the problems of missing features, blurred edges, susceptible to noise interference and unsmooth grayscale transition in traditional heterogeneous image fusion methods, a fusion method of heterogeneous images based on multi-directional gradient filtering is proposed. The method uses the multi-scale of Laplacian pyramid and the multidirection of gradient filtering to extract the details of the source image to prevent the grayscale transition from being unsmooth; an adaptive fuzzy coupling mechanism is introduced to solve the problem that the source image features are easily missing; The gradient saliency mapping strategy avoids edge blurring and noise interference. The experimental results show that the method can achieve effective fusion of heterogeneous images.
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