TY - JOUR
T1 - First-order derivative-based super-resolution
AU - Haris, Muhammad
AU - Widyanto, Muhammad Rahmat
AU - Nobuhara, Hajime
N1 - Funding Information:
This work was supported by CREST, Japan Science and Technology Agency. We would like to thank the Indonesia Endowment Fund for Education (LPDP) Scholarships from the Ministry of Finance, The Republic of Indonesia for doctoral degree scholarship.
Publisher Copyright:
© 2016, Springer-Verlag London.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - A single fast super-resolution method based on first-order derivatives from neighbor pixels is proposed. The basic idea of the proposed method is to exploit a first-order derivatives component of six edge directions around a missing pixel, followed by back projection to reduce noise estimated by the difference between simulated and observed images. Using first-order derivatives as a feature, the proposed method is expected to have low computational complexity, and it can theoretically reduce blur, blocking, and ringing artifacts in edge areas compared to previous methods. Experiments were conducted using 900 natural grayscale images from the USC-SIPI Database. We evaluated the proposed and previous methods using peak signal-to-noise ratio, structural similarity, feature similarity, and computation time. Experimental results indicate that the proposed method clearly outperforms other state-of-the-art algorithms such as fast curvature-based interpolation.
AB - A single fast super-resolution method based on first-order derivatives from neighbor pixels is proposed. The basic idea of the proposed method is to exploit a first-order derivatives component of six edge directions around a missing pixel, followed by back projection to reduce noise estimated by the difference between simulated and observed images. Using first-order derivatives as a feature, the proposed method is expected to have low computational complexity, and it can theoretically reduce blur, blocking, and ringing artifacts in edge areas compared to previous methods. Experiments were conducted using 900 natural grayscale images from the USC-SIPI Database. We evaluated the proposed and previous methods using peak signal-to-noise ratio, structural similarity, feature similarity, and computation time. Experimental results indicate that the proposed method clearly outperforms other state-of-the-art algorithms such as fast curvature-based interpolation.
KW - Back projection
KW - Edge direction
KW - First derivatives
KW - Interpolation
KW - Super-resolution
UR - http://www.scopus.com/inward/record.url?scp=84960123700&partnerID=8YFLogxK
U2 - 10.1007/s11760-016-0880-y
DO - 10.1007/s11760-016-0880-y
M3 - Article
AN - SCOPUS:84960123700
SN - 1863-1703
VL - 11
SP - 1
EP - 8
JO - Signal, Image and Video Processing
JF - Signal, Image and Video Processing
IS - 1
ER -