Texture-Aware Deblurring for Remote Sensing Images Using l(0)-Based Deblurring and l(2)-Based Fusionopen access
- Authors
- Lim, Heunseung; Yu, Soohwan; Park, Kwanwoo; Seo, Doochun; Paik, Joonki
- Issue Date
- Jun-2020
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Deblur; remote sensing; image restoration
- Citation
- IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, v.13, pp 3094 - 3108
- Pages
- 15
- Journal Title
- IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
- Volume
- 13
- Start Page
- 3094
- End Page
- 3108
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/44107
- DOI
- 10.1109/JSTARS.2020.2999961
- ISSN
- 1939-1404
2151-1535
- Abstract
- This article presents an image deblurring method using l(0)-norm-based deblurring and l(2)-norm-based texture-aware image fusion for remote sensing images. To restore the details of blurred texture, the proposed method first performs texture restoration by fusing the restored results using Richardson-Lucy deconvolution and unsharp masking. Next, we analyzed the intensity and dark channel properties of remote sensing images and perform the l(0)-norm-based deblurring using the intensity and dark channel priors. Although the l(0)-norm-based deblurring can provide a significantly restored result, it cannot overcome the loss of the texture region. On the other hand, the proposed l(2)-norm-based image fusion method can preserve both sharp edges and texture details. In the experiments, we demonstrate that the proposed method can provide better restored results than existing state-of-the-art deblurring methodswithout oversmoothing and undesired artifact.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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