Pansharpening With Matting Model
Pansharpening With Matting Model
复制标题
DOI：
10.1109/tgrs.2013.2286827
复制
发表时间：
2014-08-01
影响因子：
8.2
通讯作者：
Benediktsson, Jon Atli
中科院分区：
文献类型：
--
作者：
Kang, Xudong;Li, Shutao;Benediktsson, Jon Atli
全色锐化的目的是通过将全色（PAN）图像与多光谱（MS）图像融合，生成具有高空间分辨率和光谱分辨率的融合图像。分量替换是最广泛使用的泛锐化方法。然而，该领域的研究大多集中在改进现有的基于分量替换的泛锐化方法，如：例如，在一个实施例中，主成分替换和强度色调饱和度变换。本文的主要贡献是一个新的组件替换框架的基础上的图像抠图模型。抠图模型是指可以被分解成三个分量的MS图像，即，Alpha通道、光谱前景和背景。通过用PAN图像代替MS图像的α通道，能够完美地重建高分辨率MS图像。在不同的数据集上进行的实验表明，该方法优于几个国家的最先进的泛锐化方法的主观和客观评价。
Pansharpening aims at creating a fused image of high spatial and spectral resolutions through merging a panchromatic (PAN) image with a multispectral (MS) image. Component substitution is the most widely used pansharpening method. However, most research in this field focuses on improving the existing component substitution-based pansharpening methods, e. g., principal component substitution and intensity hue saturation transform. The major contribution of this paper is a novel component substitution framework based on an image matting model. The matting model refers to an MS image that can be decomposed into three components, i.e., alpha channel, spectral foreground, and background. Through substituting the alpha channel of the MS image with the PAN image, the high-resolution MS image is able to be reconstructed perfectly. Experiments performed on different data sets demonstrate that the proposed method outperforms several state-of-the-art pansharpening methods in terms of subjective and objective evaluation.