Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening
Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening
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DOI：
10.3389/fams.2020.00022
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发表时间：
2020-06
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影响因子：
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通讯作者：
R. Lartey;Weihong Guo;Xiaoxiang Zhu;Claas Grohnfeldt
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文献类型：
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作者：
R. Lartey;Weihong Guo;Xiaoxiang Zhu;Claas Grohnfeldt
图像超分辨率是一种图像重建技术，它试图从同一场景的一个或多个欠采样低分辨率图像重建高分辨率图像。高分辨率图像有助于在众多数字成像应用中进行分析和推断。然而，由于对高分辨率成像系统的可及性有限，因此需要替代措施来获得期望的结果。我们提出了一个三维的单图像模型，以提高图像的分辨率，通过估计模拟图像的强度函数。在最近的文献中，它已被证明，图像补丁可以表示为适当选择的基函数的线性组合。我们假设底层模拟图像由平滑和边缘分量组成，这些分量可以分别使用可再生的核希尔伯特空间函数和Heaviside函数来近似。我们还扩展了所提出的方法，泛锐化，融合高分辨率全色图像与低分辨率多光谱图像的高分辨率多光谱图像的技术。所提出的配方的各种数值结果表明竞争力的性能相比，一些国家的最先进的算法。
Image super-resolution is an image reconstruction technique which attempts to reconstruct a high resolution image from one or more under-sampled low-resolution images of the same scene. High resolution images aid in analysis and inference in a multitude of digital imaging applications. However, due to limited accessibility to high-resolution imaging systems, a need arises for alternative measures to obtain the desired results. We propose a three-dimensional single image model to improve image resolution by estimating the analog image intensity function. In recent literature, it has been shown that image patches can be represented by a linear combination of appropriately chosen basis functions. We assume that the underlying analog image consists of smooth and edge components that can be approximated using a reproducible kernel Hilbert space function and the Heaviside function, respectively. We also extend the proposed method to pansharpening, a technology to fuse a high resolution panchromatic image with a low resolution multi-spectral image for a high resolution multi-spectral image. Various numerical results of the proposed formulation indicate competitive performance when compared to some state-of-the-art algorithms.