Joint AIHS and Particle Swarm Optimization for Pan-sharpening

Autor: Yingxia CHEN,Yan CHEN,Cong LIU
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Geodesy and Geoinformation Science, Vol 3, Iss 2, Pp 105-113 (2020)
Druh dokumentu: article
ISSN: 2096-5990
DOI: 10.11947/j.JGGS.2020.0211
Popis: Pan-sharpening is a process of obtaining a high spatial and spectral multispectral image (HMS) by combining a low-resolution multispectral image (LMS) with a high-resolution panchromatic image (PAN). In this paper, a pan-sharpening method called PAIHS is proposed, which is based on adaptive intensity-hue-saturation (AIHS) transformation, variational pan-sharpening framework and the two fidelity hypotheses. The suitable objective function is established and optimized by adopting particle swarm optimization (PSO) to obtain the optimal control parameters and minimum value. This value corresponds to the best pan-sharpening quality. The experimental results show that the proposed method has high efficiency and reliability, and the obtained performance index is superior to the four mainstream pan-sharpening methods.
Databáze: Directory of Open Access Journals