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- W1969432837 abstract "Super-Resolution (SR) image reconstruction is a technology to reconstruct multiple low-resolution images into one or multiple high-resolution images. As the use of digital camera is recently increasing, the advancement of super-resolution technology gets a great attention. In this study, we propose a regularization-based Super-Resolution algorithm that utilizes an Edge-adaptive Non-Local Means filter. We compare the result of image reconstruction through the algorithm that we proposed and that of image reconstruction through existing studies. As a result, we could verify that a better result would be obtained for regularization function when using an Edge-adaptive Non-Local Means filter rather than using a Non-Local Means filter. We could also obtain much higher PSNR(Peak Signal-to Noise Ratio) than using a Bilateral Total Variation(BTV) method." @default.
- W1969432837 created "2016-06-24" @default.
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- W1969432837 date "2013-01-17" @default.
- W1969432837 modified "2023-09-24" @default.
- W1969432837 title "Regularization based super-resolution image processing algorithm using edge-adaptive non-local means filter" @default.
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- W1969432837 doi "https://doi.org/10.1145/2448556.2448634" @default.
- W1969432837 hasPublicationYear "2013" @default.
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