Image fusion by multiple features in the propagated filtering domain

IF 4.9 2区 医学 Q1 ENGINEERING, BIOMEDICAL Biomedical Signal Processing and Control Pub Date : 2024-10-25 DOI:10.1016/j.bspc.2024.106990
Jiao Du , Weisheng Li , Yidong Peng , Qianjing Zong
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Abstract

Visual high-contrast information, such as texture and color, contained in input biomedical imaging data should be preserved as much as possible in the fused image. To preserve the high-intensity textural and color information from input images, an image fusion method is proposed in this paper that utilizes propagated filtering and multiple features from the input images as two modalities. The method includes three steps. First, the inputs are decomposed into multiscale coarse images containing edge information and multiscale detail images containing textural information obtained by propagated filtering using different window sizes. Second, an entropy-based rule is used to combine the coarse images to contain much more edge information. A multiple features-based rule, including luminance, orientation and phase, is used to combine the detail images with the aim of preserving textural information and color information with less distortion. Finally, the fused image is obtained by adding the fused coarse and fused detail images in spatial-domain transformation. The experimental results on the fusion of co-registered biomedical image show that the proposed method preserves textural information with high-intensity and true color information.
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通过传播滤波域中的多重特征进行图像融合
输入生物医学成像数据中包含的视觉高对比度信息,如纹理和颜色,应尽可能保留在融合图像中。为了保留输入图像中的高强度纹理和颜色信息,本文提出了一种图像融合方法,利用传播滤波和输入图像中的多种特征作为两种模式。该方法包括三个步骤。首先,将输入图像分解为包含边缘信息的多尺度粗糙图像和包含纹理信息的多尺度细节图像,这些信息是通过使用不同窗口大小的传播滤波获得的。其次,使用基于熵的规则来组合粗图像,使其包含更多的边缘信息。然后,使用基于多个特征的规则(包括亮度、方向和相位)来组合细节图像,目的是以较小的失真保留纹理信息和色彩信息。最后,通过空间域变换将融合后的粗糙图像和融合后的细节图像相加得到融合图像。共配准生物医学图像融合的实验结果表明,所提出的方法保留了高强度的纹理信息和真实的色彩信息。
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来源期刊
Biomedical Signal Processing and Control
Biomedical Signal Processing and Control 工程技术-工程:生物医学
CiteScore
9.80
自引率
13.70%
发文量
822
审稿时长
4 months
期刊介绍: Biomedical Signal Processing and Control aims to provide a cross-disciplinary international forum for the interchange of information on research in the measurement and analysis of signals and images in clinical medicine and the biological sciences. Emphasis is placed on contributions dealing with the practical, applications-led research on the use of methods and devices in clinical diagnosis, patient monitoring and management. Biomedical Signal Processing and Control reflects the main areas in which these methods are being used and developed at the interface of both engineering and clinical science. The scope of the journal is defined to include relevant review papers, technical notes, short communications and letters. Tutorial papers and special issues will also be published.
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