A self-learning approach for pan-sharpening of multispectral images

Khateri, Mohammad; Ghassemian, Hassan

doi:10.1109/icsipa.2017.8120606

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…Khateri M and Ghassemian H [22] designed a self-learning approach for pan-sharpening lowresolution MS images. Here, numerous structures from the natural language were applied in a repetitive manner fat multiple scale.…”

Section: Image Fusion-based Techniquesmentioning

confidence: 99%

“…The introduced approach in [19] failed to consider loss functions for training the network with typical no-reference measures in order to enhance the pan-sharpening performance. In [22], the major challenge lies in utilizing optimization-driven techniques for enhancing network performance. The research problems faced by the Guided filterenabled techniques are as follows, the designed approach in [21] failed to improve the spatial resolution images to protect the spectral information.…”

Section: Research Gaps and Issuesmentioning

confidence: 99%

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Study and Analysis of Various Pan-Sharpening Techniques: A Challenging Overview

Singh¹

2022

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Satellite sensors acquire massive data to exploit and address numerous human tasks. Due to the physical constraints, the usage of high spatial resolution multispectral (MS) images cannot be acquired by the unique devices. Hence, it is necessary to develop techniques by incorporating the images of MS and the panchromatic (PAN), also called Pan sharpening in remote sensing applications. Hence, this survey analyzes 30 research existing papers in Pan sharpening, which is based on various techniques, like neural network-based techniques, image fusion-based techniques, guided filterbased techniques, and optimization-based techniques. The analysis is based on the publication year of the research paper, research techniques employed, performance evaluation measures, and achievement of the research techniques. Also, the issues in the approaches are explained. Moreover, the future scope is to develop an efficient Pan sharpening technique based on the limitations recognized from the existing research Pan sharpening techniques.

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Section: Image Fusion-based Techniquesmentioning

confidence: 99%

Section: Research Gaps and Issuesmentioning

confidence: 99%

Study and Analysis of Various Pan-Sharpening Techniques: A Challenging Overview

Singh¹

2022

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“…In [32], the discrete ripplet used as transformation and compressed sensing exploited in the injecting details from HRP image to the intensity component. Recently, we introduced a self‐learning approach to estimate intensity component using self‐similarity of structures in the different image resolutions [33]. Saxena and Sharma [34] fortified the intensity component through Hilbert vibration decomposition.…”

Section: Introductionmentioning

confidence: 99%