A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery

Javan, Farzaneh Dadrass; Samadzadegan, Farhad; Mehravar, Saeed; Toosi, Ahmad; Khatami, Reza; Stein, Alfred

doi:10.1016/j.isprsjprs.2020.11.001

Cited by 129 publications

(58 citation statements)

References 122 publications

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“…With the rapid development of computer technology, image fusion technology has played a vital role in medical diagnosis, monitoring, transportation, and other fields. Among them, in the research in the medical field, this technology has received extensive attention [ 5 – 9 ].…”

Section: Introductionmentioning

confidence: 99%

Application of Multimodal Fusion Technology in Image Analysis of Pretreatment Examination of Patients with Spinal Injury

Guo-cheng

Zhang

et al. 2022

Journal of Healthcare Engineering

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As one of the most common imaging screening techniques for spinal injuries, MRI is of great significance for the pretreatment examination of patients with spinal injuries. With rapid iterative update of imaging technology, imaging techniques such as diffusion weighted magnetic resonance imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and magnetic resonance spectroscopy are frequently used in the clinical diagnosis of spinal injuries. Multimodal medical image fusion technology can obtain richer lesion information by combining medical images in multiple modalities. Aiming at the two modalities of DCE-MRI and DWI images under MRI images of spinal injuries, by fusing the image data under the two modalities, more abundant lesion information can be obtained to diagnose spinal injuries. The research content includes the following: (1) A registration study based on DCE-MRI and DWI image data. To improve registration accuracy, a registration method is used, and VGG-16 network structure is selected as the basic registration network structure. An iterative VGG-16 network framework is proposed to realize the registration of DWI and DCE-MRI images. The experimental results show that the iterative VGG-16 network structure is more suitable for the registration of DWI and DCE-MRI image data. (2) Based on the fusion research of DCE-MRI and DWI image data. For the registered DCE-MRI and DWI images, this paper uses a fusion method combining feature level and decision level to classify spine images. The simple classifier decision tree, SVM, and KNN were used to predict the damage diagnosis classification of DCE-MRI and DWI images, respectively. By comparing and analyzing the classification results of the experiments, the performance of multimodal image fusion in the auxiliary diagnosis of spinal injuries was evaluated.

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Section: Introductionmentioning

confidence: 99%

Application of Multimodal Fusion Technology in Image Analysis of Pretreatment Examination of Patients with Spinal Injury

Guo-cheng

Zhang

et al. 2022

Journal of Healthcare Engineering

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“…We fused the high-resolution spatial structure from LISS III with the low-resolution spectral information from Landsat to construct a high-resolution multispectral image for land use and landcover classification. The idea of fusion algorithms is to sharpen the remotely sensed data by enhancing edges and grey level discontinuities without making changes on multispectral components in homogeneous areas [48]. Two things need to be taken care of to facilitate these requirements, as (i) optimal colour and spatial details must be separated and (ii) spatial information should be manipulated to allow adaptive enhancement of images [49].…”

Section: Image Fusionmentioning

confidence: 99%

“…Two things need to be taken care of to facilitate these requirements, as (i) optimal colour and spatial details must be separated and (ii) spatial information should be manipulated to allow adaptive enhancement of images [49]. The IHS transform is used for optimal colour separation similarly when the number of bands available is three, multiple IHS transform is employed until the number of bands available [48]. Since the spectral characteristics of every band varies, the order of bands must be specified for IHS transform [44].…”

Section: Image Fusionmentioning

confidence: 99%

Using Satellite Image Fusion to Evaluate the Impact of Land Use Changes on Ecosystem Services and Their Economic Values

Wang¹,

Padmanaban

Mbanze

et al. 2021

Remote Sensing

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Accelerated land use change is a current challenge for environmental management worldwide. Given the urgent need to incorporate economic and ecological goals in landscape planning, cost-effective conservation strategies are required. In this study, we validated the benefit of fusing imagery from multiple sensors to assess the impact of landscape changes on ecosystem services (ES) and their economic values in the Long County, Shaanxi Province, China. We applied several landscape metrics to assess the local spatial configuration over 15 years (2004–2019) from fused imageries. Using Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Landsat-8 Operational Land Imager (OLI) and Indian Remote Sensing Satellite System Linear Imaging Self Scanning Sensor 3 (IRS LISS 3) imageries fused for 2004, 2009, 2014 and 2019, we reclassified land use/land cover (LULC) changes, through the rotation forest (RF) machine-learning algorithm. We proposed an equivalent monetary metric for estimating the ES values, which also could be used in the whole China. Results showed that agriculture farmland and unused land decreased their spatial distribution over time, with an observed increase on woodland, grassland, water bodies and built-up area. Our findings suggested that the patterns of landscape uniformity and connectivity improved, while the distribution of landscape types stabilized, while the landscape diversity had a slight improvement. The overall ES values increased (4.34%) under a benefit transfer approach, mainly concerning woodland and grassland. A sensitivity analysis showed the selected economic value (EV) was relevant and suitable for the study area associated with our ES for LULC changes. We suggested that changes in landscape patterns affected the ESV trends, while the increases on some LULC classes slightly improved the landscape diversity. Using an interdisciplinary approach, we recommend that local authorities and environmental practitioners should balance the economic benefits and ecological gains in different landscapes to achieve a sustainable development from local to regional scales.

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“…We can take GAN as one of the special instances. Please refer to [56] in which the authors make a comprehensive review of Pan-sharpening satellite imagery.…”

Section: Red-cgan [53]mentioning

confidence: 99%

A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)

Liu¹

2021

Preprint

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In the past decades, remote sensing (RS) data fusion has always been an active research community. A large number of algorithms and models have been developed. Generative Adversarial Networks (GAN), as an important branch of deep learning, show promising performances in variety of RS image fusions. This review provides an introduction to GAN for remote sensing data fusion. We briefly review the frequently-used architecture and characteristics of GAN in data fusion and comprehensively discuss how to use GAN to realize fusion for homogeneous RS data, heterogeneous RS data, and RS and ground observation data. We also analyzed some typical applications with GAN-based RS image fusion. This review takes insight into how to make GAN adapt to different types of fusion tasks and summarizes the advantages and disadvantages of GAN-based RS data fusion. Finally, we discuss the promising future research directions and make a prediction on its trends.

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A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery

Cited by 129 publications

References 122 publications

Application of Multimodal Fusion Technology in Image Analysis of Pretreatment Examination of Patients with Spinal Injury

Application of Multimodal Fusion Technology in Image Analysis of Pretreatment Examination of Patients with Spinal Injury

Using Satellite Image Fusion to Evaluate the Impact of Land Use Changes on Ecosystem Services and Their Economic Values

A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)

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