Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening
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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-06-01
|
| Series: | Frontiers in Applied Mathematics and Statistics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fams.2020.00022/full |
| _version_ | 1818514817984495616 |
|---|---|
| author | Richard Lartey Weihong Guo Xiaoxiang Zhu Claas Grohnfeldt |
| author_facet | Richard Lartey Weihong Guo Xiaoxiang Zhu Claas Grohnfeldt |
| author_sort | Richard Lartey |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T00:20:56Z |
| format | Article |
| id | doaj.art-c33c0aaad822493fb3e2e6068f1ceb9a |
| institution | Directory Open Access Journal |
| issn | 2297-4687 |
| language | English |
| last_indexed | 2024-12-11T00:20:56Z |
| publishDate | 2020-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Applied Mathematics and Statistics |
| spelling | doaj.art-c33c0aaad822493fb3e2e6068f1ceb9a2022-12-22T01:27:46ZengFrontiers Media S.A.Frontiers in Applied Mathematics and Statistics2297-46872020-06-01610.3389/fams.2020.00022531776Analog Image Modeling for 3D Single Image Super Resolution and PansharpeningRichard Lartey0Weihong Guo1Xiaoxiang Zhu2Claas Grohnfeldt3Department of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, OH, United StatesDepartment of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, OH, United StatesGerman Aerospace Center (DLR), Wessling, GermanyDepartment of Aerospace and Geodesy, Technical University of Munich, Munich, GermanyImage 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.https://www.frontiersin.org/article/10.3389/fams.2020.00022/fullsuper-resolutionreproducible kernel Hilbert space (RKHS)heavisidesparse representationmultispectral imaging |
| spellingShingle | Richard Lartey Weihong Guo Xiaoxiang Zhu Claas Grohnfeldt Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening Frontiers in Applied Mathematics and Statistics super-resolution reproducible kernel Hilbert space (RKHS) heaviside sparse representation multispectral imaging |
| title | Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening |
| title_full | Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening |
| title_fullStr | Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening |
| title_full_unstemmed | Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening |
| title_short | Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening |
| title_sort | analog image modeling for 3d single image super resolution and pansharpening |
| topic | super-resolution reproducible kernel Hilbert space (RKHS) heaviside sparse representation multispectral imaging |
| url | https://www.frontiersin.org/article/10.3389/fams.2020.00022/full |
| work_keys_str_mv | AT richardlartey analogimagemodelingfor3dsingleimagesuperresolutionandpansharpening AT weihongguo analogimagemodelingfor3dsingleimagesuperresolutionandpansharpening AT xiaoxiangzhu analogimagemodelingfor3dsingleimagesuperresolutionandpansharpening AT claasgrohnfeldt analogimagemodelingfor3dsingleimagesuperresolutionandpansharpening |