基于域转移和非刚性变换的多模态图像融合

Yicheng Yang, Huabing Zhou
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引用次数: 0

摘要

红外图像可以根据热辐射的差异来区分目标和背景,在昼夜和各种天气条件下都能很好地工作。相比之下,可见图像可以以符合人类视觉系统的方式提供具有高空间分辨率和清晰度的纹理细节。我们通过三个步骤解决了多模态图像融合问题。首先,引入域转移技术,将图像从一个域转移到另一个域。例如,从可见光图像到红外图像。它可以捕获一个图像集的内容特征,并找出如何将这些特征转化为另一个图像集,所有这些都没有任何配对的训练示例。其次,采用非刚性变换方法对域转移图像与目标图像进行匹配,使图像对在像素级上对齐;然后重点对域转移和空间变换后的图像与目标图像进行融合。通过平移和变换,将融合问题简化为一个简单的组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image fusion for multimodality image via domain transfer and nonrigid transformation
Infrared images can distinguish targets from their backgrounds on the basis of difference in thermal radiation, which works well at all day/night time and under all weather conditions. By contrast, visible images can provide texture details with high spatial resolution and definition in a manner consistent with the human visual system. We addressed the multimodality image fusion problem through three steps. Firstly, Domain transfer technique is introduced to transfer an image from one domain to another. For example, from visible image to infrared image. It can capture content characteristics of one image collection and figure out how these characteristics could be translated into the other image collection, all in the absence of any paired training examples. Secondly, we employ the nonrigid transformation method to match the domain transferred image and the target image, let the images pairs align in pixel level. Then we focus on fusion the domain transferred and spatial transformed image with the target image. Through translation and transformation, we simplify the fusion problem into a simple combination.
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