Image Fusion in Remote Sensing Applications: A Review
Vaibhav R. Pandit,R. J. Bhiwani +1 more
TLDR
This paper is an honest attempt to collectively discuss all possible algorithms along with quality metrics following two assessment procedures i.e. at full and reduced scale resolutions to evaluate performance of these algorithms.Abstract:
Major technical constraints like minimum data storage at satellite platform in space, less bandwidth for communication with earth station, etc. limits the satellite sensors from capturing images with high spatial and high spectral resolutions simultaneously. To overcome this limitation, image fusion has proved to be a potential tool in remote sensing applications which integrates the information from combinations of panchromatic, multispectral or hyperspectral images; intended to result in a composite image having both higher spatial and higher spectral resolutions. The research in this area cites date back to last few decades, but the diverse approaches proposed so far by different researchers have been rarely discussed at one place. This paper is an honest attempt to collectively discuss all possible algorithms along with quality metrics following two assessment procedures i.e. at full and reduced scale resolutions to evaluate performance of these algorithms.read more
Citations
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High PSNR based Image Fusion by use Brovey Transform
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Dimensionality Reduction and Vegetation Monitoring On LISS III Satellite Image Using Principal Component Analysis and Normalized Difference Vegetation Index
TL;DR: In this paper, principal component analysis (PCA) and Normalized Difference Vegetation Index (NDVI) were used for analyzing the LISS III satellite image, acquired from the region of Tirpattur district in Tamil Nadu, India.
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A Learning-Based Image Fusion for High-Resolution SAR and Panchromatic Imagery
Dae Kyo Seo,Yang Dam Eo +1 more
TL;DR: The experimental results show that the proposed novel fusion method is superior in terms of visual and quantitative aspects, thus verifying its applicability, and the performance of the proposed method is evaluated by comparison with conventional methods.
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Weighted principal component analysis fusion of satellite telemetry data
TL;DR: This paper presents a novel weighted reliability with rejection control PCA based sensor algorithm to improve data fusion quality creating a more robust visualization of the composite information obtained from satellites.
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Oil spill segmentation in fused Synthetic Aperture Radar images
TL;DR: An automatic feature based image registration and fusion algorithm for oil spill monitoring using SAR images that has shown 45% improvement of the oil spill location when compared with the individual images before the fusion.
References
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Journal ArticleDOI
Multisensor image fusion using the wavelet transform
TL;DR: In this article, an image fusion scheme based on the wavelet transform is presented, where wavelet transforms of the input images are appropriately combined, and the new image is obtained by taking the inverse wavelet transformation of the fused wavelet coefficients.
Journal ArticleDOI
A Critical Comparison Among Pansharpening Algorithms
Gemine Vivone,Luciano Alparone,Jocelyn Chanussot,Mauro Dalla Mura,Andrea Garzelli,Giorgio Licciardi,Rocco Restaino,Lucien Wald +7 more
TL;DR: The authors attempt to fill the gap by providing a critical description and extensive comparisons of some of the main state-of-the-art pansharpening methods by offering a detailed comparison of their performances with respect to the different instruments.
Journal ArticleDOI
A comparative analysis of image fusion methods
TL;DR: This paper presents a comprehensive framework, the general image fusion (GIF) method, which makes it possible to categorize, compare, and evaluate the existing image fusion methods.
Journal ArticleDOI
Local Binary Patterns and Extreme Learning Machine for Hyperspectral Imagery Classification
TL;DR: The proposed framework employs local binary patterns to extract local image features, such as edges, corners, and spots, and employs the efficient extreme learning machine with a very simple structure as the classifier.