Multi-resolution image fusion using multistage guided filter

Sharad Joshi, Kishor P. Upla, M. Joshi
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引用次数: 4

Abstract

In this paper, we propose a multi-resolution image fusion approach based on multistage guided filter (MGF). Given the high spatial resolution panchromatic (Pan) and high spectral resolution multi-spectral (MS) images, the multi-resolution image fusion algorithm obtains a single fused image having both the high spectral and the high spatial resolutions. Here, we extract the missing high frequency details of MS image by using multistage guided filter. The detail extraction process exploits the relationship between the Pan and MS images by utilizing one of them as a guidance image and extracting details from the other. This way the spatial distortion of MS image is reduced by consistently combining the details obtained using both types of images. The final fused image is obtained by adding the extracted high frequency details to corresponding MS image. The results of the proposed algorithm are compared with the commonly used traditional methods as well as with a recently proposed method using Quickbird, Ikonos-2 and Worldview-2 satellite images. The quantitative assessment is evaluated using the conventional measures as well as using a relatively new index i.e., quality with no reference (QNR) which does not require a reference image. The results and measures clearly show that there is significant improvement in the quality of the fused image using the proposed approach.
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基于多级引导滤波器的多分辨率图像融合
本文提出了一种基于多级引导滤波(MGF)的多分辨率图像融合方法。针对高空间分辨率全色(Pan)图像和高光谱分辨率多光谱(MS)图像,采用多分辨率图像融合算法得到高光谱分辨率和高空间分辨率的融合图像。在这里,我们使用多级引导滤波器提取MS图像中缺失的高频细节。细节提取过程利用Pan和MS图像之间的关系,利用其中一幅图像作为引导图像,从另一幅图像中提取细节。这样,通过一致地结合使用两种类型的图像获得的细节,减少了MS图像的空间畸变。将提取的高频细节与相应的MS图像相加,得到最终的融合图像。将该算法与常用的传统方法进行了比较,并与最近提出的基于Quickbird、Ikonos-2和Worldview-2卫星图像的方法进行了比较。定量评估使用传统的措施,以及使用一个相对较新的指标,即质量无参考(QNR),不需要参考图像进行评估。结果和测量清楚地表明,使用该方法融合图像的质量有显着提高。
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