A Variational Approach for Fusion of Panchromatic and Multispectral Images Using a New Spatial–Spectral Consistency Term

Abstract

In this paper, we propose a variational approach for fusion of two co-registered high-resolution panchromatic (HRP) and low-resolution multi-spectral (LRM) images to reach the high-resolution multi-spectral (HRM) one, i.e. pan-sharpening. In this fusion technique, there is a trade-off between structural information of HRP image and spectral information of LRM one. To reconstruct the HRM image, which benefits from the best characteristics of both images, we consider several fidelity terms. The structural fidelity term is used to transfer structural information of HRP image to HRM one, and spectral fidelity term is utilized to preserve spectral consistency between HRM and LRM images throughout the fusion process. To reduce the spectral distortion occurred due to the discrepancy between intensity values of HRP and LRM images, a novel spatial-spectral fidelity term is designed to keep the intensity ratio between multispectral and panchromatic pixels in the high-resolution space as the same as the low-resolution space. Moreover, the total variation (TV) regularization term is employed as a prior to promote the sparseness of gradient in HRM bands. These fidelity terms were formulated in a convex optimization problem. However, the structural and TV terms made this optimization problem nondifferentiable. Therefore, we developed an efficient majorizationminimization (MM) algorithm for solving the optimization problem. The proposed method applied to three datasets, acquired by WorldView-3, Deimos-2, and QuickBird satellites. To assess the effectiveness of the proposed method, visual analysis, as well as quantitative comparison to various pan-sharpening methods, were carried out. The experimental results suggested that the proposed method outperformed the competitors visually and quantitatively.

Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

“…This work is focused on Deimos-2 sensor, a VHR optical satellite operated by Deimos Imaging that launched on 19 June 2014. There are only a few published works dealing with pansharpening methods [ 14 ] or image classification [ 15 ] from Deimos-2 imagery. Regarding the geometric capabilities of the Deimos-2 level 1B (L1B) product, a technical report was published by the Joint Research Centre (JRC) in the frame of control with the remote sensing program of the European Common Agriculture Policy [ 16 ].…”