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A high-resolution panchromatic-multispectral satellite image fusion method assisted with building segmentation
Journal article   Open access   Peer reviewed

A high-resolution panchromatic-multispectral satellite image fusion method assisted with building segmentation

Fang Gao, Yihui Li, Peng Zhang, Yuwei Zhai, Yan Zhang, Yongshuai Yang and Yuan An
Computers & geosciences, v 168, p105219
01 Nov 2022
url
https://doi.org/10.1016/j.cageo.2022.105219View
Published, Version of Record (VoR) Open

Abstract

Computer Science Computer Science, Interdisciplinary Applications Geology Geosciences, Multidisciplinary Physical Sciences Science & Technology Technology
The main difficulty of panchromatic-multispectral image fusion is to balance the quality of spatial information and the spectral fidelity. Most of the practical fusion methods determine the optimal parameters based on the spatial and spectral characteristics of all original panchromatic and multispectral bands. However, for built-up and non-built-up areas (like cropland, forest) in one image, there may be large differences in their spatial and spectral characteristics, so their fused results are not optimal respectively with same parameters. To address above issues, this paper presents a high-resolution satellite image fusion method assisted with building segmentation. First, the proposed approach computes the average gradient and Gaussian filtering parameters of built-up and non-built-up areas separately according to the building segmentation results, on the basis of smoothing filter-based intensity modulation (SFIM). Then the intermediate data of two types of areas are computed in parallel and they are composited to obtain the final fused image, weighted by the pixel-wise "building factors" derived from the building segmentation results. Moreover, to better simulate the spatial characteristics of the multispectral image, we perform the "gradient simulation" operation to extract the gradient values in the multispectral image. Experimental results on Jilin-1 satellite images show that the proposed method provides competitive performance in spatial resolution, multispectral fidelity and quantity of information, as compared to the state-of-the-art methods in mainstream commercial software.

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Web of Science research areas
Computer Science, Interdisciplinary Applications
Geosciences, Multidisciplinary
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