Meng Xiangchao, Li Jie, Shen Huanfeng, Zhang Liangpei, Zhang Hongyan
School of Resource and Environmental Sciences, Wuhan University, Luoyu Road, Wuhan 430079, China.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road, Wuhan 430079, China.
Sensors (Basel). 2016 Jul 12;16(7):1068. doi: 10.3390/s16071068.
State-of-the-art pansharpening methods generally inject the spatial structures of a high spatial resolution (HR) panchromatic (PAN) image into the corresponding low spatial resolution (LR) multispectral (MS) image by an injection model. In this paper, a novel pansharpening method with an edge-preserving guided filter based on three-layer decomposition is proposed. In the proposed method, the PAN image is decomposed into three layers: A strong edge layer, a detail layer, and a low-frequency layer. The edge layer and detail layer are then injected into the MS image by a proportional injection model. In addition, two new quantitative evaluation indices, including the modified correlation coefficient (MCC) and the modified universal image quality index (MUIQI) are developed. The proposed method was tested and verified by IKONOS, QuickBird, and Gaofen (GF)-1 satellite images, and it was compared with several of state-of-the-art pansharpening methods from both qualitative and quantitative aspects. The experimental results confirm the superiority of the proposed method.
先进的全色锐化方法通常通过注入模型将高空间分辨率（HR）全色（PAN）图像的空间结构注入到相应的低空间分辨率（LR）多光谱（MS）图像中。本文提出了一种基于三层分解的具有边缘保留引导滤波器的新型全色锐化方法。在所提出的方法中，将PAN图像分解为三层：强边缘层、细节层和低频层。然后通过比例注入模型将边缘层和细节层注入到MS图像中。此外，还开发了两个新的定量评估指标，包括修正相关系数（MCC）和修正通用图像质量指数（MUIQI）。所提出的方法通过IKONOS、QuickBird和高分（GF）-1卫星图像进行了测试和验证，并从定性和定量方面与几种先进的全色锐化方法进行了比较。实验结果证实了所提出方法的优越性。
