Pansharpening algorithm via gradient domain PCNN and weighted mean curvature filtering

Wei Tan; Jiajia Zhao; Xinkai Liang; Zhongshi Lv; Hanchen Lu

doi:10.1117/12.2648382

23 January 2023 Pansharpening algorithm via gradient domain PCNN and weighted mean curvature filtering

Wei Tan, Jiajia Zhao, Xinkai Liang, Zhongshi Lv, Hanchen Lu

Proceedings Volume 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology; 125570V (2023) https://doi.org/10.1117/12.2648382
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Remote sensing images obtained from a single sensor have the disadvantage of incomplete information in terms of either low spatial resolutions or low spectral resolutions. To overcome this disadvantage, a pansharpening algorithm based on weighted mean curvature filtering (WMCF) and dual-channel pulse-coupled neural network (PCNN) in multi-scale morphological gradient (MSMG) domain is proposed in this paper. Firstly, the PAN image is decomposed into three parts, a small-scale image, a large-scale image, and a base image through a WMCF-based decomposition model. Then, a PCNN fusion strategy modulated by MSMG is used to fuse the base image and each band of the MS image. Finally, each fused bands are combined to obtain the final fused image. Experiments in four datasets demonstrate that the proposed algorithm obtains the best performance in most cases.

Citation Download Citation

Wei Tan, Jiajia Zhao, Xinkai Liang, Zhongshi Lv, and Hanchen Lu "Pansharpening algorithm via gradient domain PCNN and weighted mean curvature filtering", Proc. SPIE 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology, 125570V (23 January 2023); https://doi.org/10.1117/12.2648382

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KEYWORDS

Image fusion

Remote sensing

Image filtering

Visualization

Gaussian filters

Neural networks

Spatial resolution

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