@inproceedings{Wonseok2013,
abstract = {This paper presents a novel real-time super-resolution (SR) method using directionally adaptive image interpolation and image restoration. The proposed interpolation method estimates the edge orientation using steerable filters and performs edge refinement along the estimated edge orientation. Bi-linear and bi-cubic interpolation filters are then selectively used according to the estimated edge orientation for reducing jagging artifacts in slanting edge regions. The proposed restoration method can effectively remove image degradation caused by interpolation using the directionally adaptive truncated constrained least-squares (TCLS) filter. The proposed method provides high-quality magnified images which are similar to or better than the result of advanced interpolation or SR methods without high computational load. Experimental results indicate that the proposed system gives higher peak-to-peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) values than the state-of-the-art image interpolation methods. {\textcopyright} 2013 IEEE.},
author = {Kang, Wonseok and Jeon, Jaehwan and Lee, Eunsung and Cho, Changhun and Jung, Junghoon and Kim, Taechan and Katsaggelos, Aggelos K. and Paik, Joonki},
booktitle = {2013 IEEE International Conference on Image Processing},
doi = {10.1109/ICIP.2013.6738270},
isbn = {978-1-4799-2341-0},
keywords = {Super-resolution,digital zooming,image interpolation,image restoration},
month = {sep},
pages = {1311--1315},
publisher = {IEEE},
title = {{Real-time super-resolution for digital zooming using finite kernel-based edge orientation estimation and truncated image restoration}},
url = {http://ieeexplore.ieee.org/document/6738270/},
year = {2013}
}

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The proposed restoration method can effectively remove image degradation caused by interpolation using the directionally adaptive truncated constrained least-squares (TCLS) filter. The proposed method provides high-quality magnified images which are similar to or better than the result of advanced interpolation or SR methods without high computational load. 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The proposed interpolation method estimates the edge orientation using steerable filters and performs edge refinement along the estimated edge orientation. Bi-linear and bi-cubic interpolation filters are then selectively used according to the estimated edge orientation for reducing jagging artifacts in slanting edge regions. The proposed restoration method can effectively remove image degradation caused by interpolation using the directionally adaptive truncated constrained least-squares (TCLS) filter. The proposed method provides high-quality magnified images which are similar to or better than the result of advanced interpolation or SR methods without high computational load. 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