https://scholars.lib.ntu.edu.tw/handle/123456789/607197
標題: | Border Compensation Scheme for Image Deblurring | 作者: | Hua S.-C. JIAN-JIUN DING |
關鍵字: | artifact removal;border compensation;computation photography;Gaussian extension model;image deblurring;Gaussian distribution;Artifact removal;Border compensation;Compensation mechanism;Compensation scheme;Computation photography;Extension models;Gaussians;Image deblurring;Image processing problems;Image enhancement | 公開日期: | 2021 | 起(迄)頁: | 221-224 | 來源出版物: | Proceedings of the 3rd IEEE Eurasia Conference on IOT, Communication and Engineering 2021, ECICE 2021 | 摘要: | Border compensation is critical for many image processing problems, including image deblurring. Without a proper border compensation mechanism, the border is misidentified as a high-frequency component, and artifacts may be generated after image deblurring. There are several existing border compensation methods, including zero padding, border repetition, mirror reflection, and slope extension. However, all of these methods inevitably have artifact problems due to the discontinuity of higher-order differences. In this work, we propose an alternative border compensation model by using the Gaussian extension model. Since the derivative of the Gaussian function at the center is zero no matter what the order of the derivative is, using the proposed algorithm much reduces the artifact around the border. Experiment results show that, with the proposed border extension scheme, the image deblurring results have much less artifact. It is helpful for image quality improvement and computer vision. ? 2021 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124214768&doi=10.1109%2fECICE52819.2021.9645723&partnerID=40&md5=a2070f015a79ee6dedb1bbe06d625e6c https://scholars.lib.ntu.edu.tw/handle/123456789/607197 |
DOI: | 10.1109/ECICE52819.2021.9645723 |
顯示於: | 電機工程學系 |
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