Pan-sharpening with a spatial-enhanced variational model

Weisheng Li; Qiujun Hu; Liping Zhang; Jiao Du

doi:10.1117/1.JRS.12.035018

24 September 2018 Pan-sharpening with a spatial-enhanced variational model

Weisheng Li, Qiujun Hu, Liping Zhang, Jiao Du

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 3, 035018 (September 2018). https://doi.org/10.1117/1.JRS.12.035018

Abstract

Pan-sharpening is a procedure that fuses a low-resolution multispectral (MS) image and a high-resolution panchromatic (PAN) image into a high-resolution MS image. Existing variational pan-sharpening methods typically consider gradient as the descriptor of the spatial information and enforce this to be consistent between the PAN image and fused image because of their shared scenes. However, the gradient feature is not sufficient to exploit the abundant spatial details. Second-order derivative, which is balanced with the first-order derivative, is introduced to build a variational model such that additional geographic information is extracted from the PAN image. Then corresponding numerical schemes to determine the minimal solution of this model are provided. Through experiments on data from four different satellites, the proposed method is proven to enhance the spatial quality of the fused result and demonstrate stable performance in preserving the spectral information.

Citation Download Citation

Weisheng Li, Qiujun Hu, Liping Zhang, and Jiao Du "Pan-sharpening with a spatial-enhanced variational model," Journal of Applied Remote Sensing 12(3), 035018 (24 September 2018). https://doi.org/10.1117/1.JRS.12.035018

Received: 26 June 2018; Accepted: 5 September 2018; Published: 24 September 2018

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available