Manifold regularized sparse representation of injected details for pansharpening

Fei, Rongrong; Zhang, Jiangshe; Liu, Junmin; Du, Fang; Chang, Peiju; Hu, Jie

doi:10.1080/01431161.2019.1610984

Cited by 5 publications

(1 citation statement)

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“…Benefiting from the development of sparse representation theory in signal science, its theory has also been applied in the field of remotesensing image fusion. Unlike the rest of the VO class of methods, the sparse representation approach considers that HRMS images can be obtained by constructing an overcomplete dictionary of high-resolution multispectral images and their sparse coefficients [26]. Most of the subsequent studies have focused on how to construct overcomplete dictionaries.…”

Section: Introductionmentioning

confidence: 99%

A Spectral Enhancement Method Based on Remote-Sensing Images for High-Speed Railways

Zuo

Qiu

et al. 2023

Electronics

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This paper proposes a pansharpening model in order to obtain remote-sensing images with high spatial resolution and high spectral resolution. Based on a generic component substitution (CS) fusion framework, the model utilizes the difference between the high-frequency component of the panchromatic (PAN) image and the high-frequency component of the luminance (L) image to express the missing spatial detail information of the ideal high-resolution multispectral (HRMS) image. A rolling guidance filter (RGF) is used in this framework to achieve the effective extraction of high-frequency information from remote-sensing images while reducing the spectral distortion of subsequent operations. The modulation transfer function (MTF) values of the sensor are also applied to the selection of adaptive weighting coefficients to further improve the spectral fidelity of the fused images. At the same time, the choice of suitable interpolation and gain coefficients improves the generalizability of the model while reducing spectral and spatial distortions. Finally, the use of a guided filter (GF) also greatly improves the quality of the fused image. The experimental results show that the model can effectively improve the spatial resolution for foreign objects at the perimeter of high-speed railways, while also ensuring the color fidelity of foreign objects such as colored steel tiles.

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Section: Introductionmentioning

confidence: 99%