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基于热物理特性的地球静止气象卫星可见光与红外图像直接融合

Direct fusion of geostationary meteorological satellite visible and infrared images based on thermal physical properties.

作者信息

Han Lei, Wulie Buzha, Yang Yiling, Wang Hongqing

机构信息

School of Information Science and Engineering, Ocean University of China, 238 Songling Road, Qingdao 266100, China.

Department of Atmospheric and Oceanic Science, Peking University, Beijing 100871, China.

出版信息

Sensors (Basel). 2015 Jan 5;15(1):703-14. doi: 10.3390/s150100703.

Abstract

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion.

摘要

本研究探讨了一种融合可见光(VIS)和红外(IR)图像的新方法,其主要目标是获得更高分辨率的红外图像。大多数现有的图像融合方法仅关注视觉性能,许多方法未能考虑红外图像的热物理特性,导致融合图像出现光谱失真。在本研究中,我们利用红外热物理特性直接校正可见光图像。具体而言,斯特藩-玻尔兹曼定律被用作一个强大的约束条件来调制可见光图像,使得融合结果显示出与原始红外图像相似水平的区域热能,同时保留来自可见光图像的高分辨率结构特征。该方法是对我们之前研究的改进,之前的研究在应用相同的校正方法之前需要进行可见光-红外多小波融合。实验结果表明,直接对可见光图像应用此校正而不进行多分辨率分析(MRA)处理可获得相似的结果,但计算效率要高得多,从而为可见光和红外图像融合提供了一个新的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49fa/4327044/97e7523dff3b/sensors-15-00703f1.jpg

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