Background Aware Correlation Filter (BACF) tracker achieves accurate tracking result in visual object tracking by mitigating boundary effects, yet is limited in challenging scenarios especially in viewpoint change and illumination variation, which are frequently encountered in Unmanned Aerial Vehicle (UAV) tracking tasks. To address the shortcomings, we propose a Foreground Aware Correlation Filter with adaptive feature response fusion (FACF). In this paper, we use saliency detection to generate foreground prior knowledge in training phase for suppressing potential noise. Furthermore, recognizing the limitation of BACF, which relies on a single feature, a novel adaptive fusion strategy is designed to fuse multiple feature responses during the detection phase. This strategy aims to enhance the robustness of the tracker. Extensive experiments have been conducted on three challenging benchmarks. The tracking results show that the proposed tracker performs accurate and robust tracking result and satisfies real-time requirement with 48.28fps.

In this article, a new variational pansharpening method based on kernel estimation and regional extended low rank is proposed, which aims to generate a high resolution multispectral (HRMS) image by fusing the panchromatic (PAN) and multispectral (MS) image. First, an estimated blurring kernel is generated for the spectral constraint term, which can build the relationship between the MS and HRMS image more accurately and improve the spectral quality of the HRMS image. Second, a spatial constrain term is designed by adopting the proportional relationship of the PAN and HRMS image in gradient domain, which preserves the geometric information of the PAN image well. Third, according to sensor imaging principle, a prior constraint term is proposed based on regional extended low rank, which can improve the spatial clarity of HRMS image. The above three constraint terms are combined to form the proposed variational pansharpening method, and the ADMM method is applied for solving it. Finally, experiments show the effectiveness of the proposed method through comparing with other state-of-art pansharpening methods.