TY - GEN
T1 - Image interpolation by using Gaussian regularized regression with cross-based window
AU - Chou, Yang Ting
AU - Chiou, Shu Huei
AU - Yang, Jar Ferr
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/1/5
Y1 - 2016/1/5
N2 - To increase resolutions, image interpolation has been widely investigated for several years. Especially, the interpolation techniques for super resolution televisions become more and more important since the most video programs are only with high definition. The linear-based interpolation algorithms bring out the jaggy noise conspicuously. Recently, the new edge-directed interpolation (NEDI) is proposed to improve the accuracy with one-fold training size for predicting parameters. In this paper, an image interpolation based on Gaussian regularized regression with cross-based window (GRR-CW) approach is proposed. The GRR-CW contains spatial confidence consideration and cross-based window generation to lead the prediction more reliable. In experimental results, we prove that the proposed GRR-CW can achieve higher image quality in PSNR and SSIM performances than the traditional linear-based and NEDI-based algorithms.
AB - To increase resolutions, image interpolation has been widely investigated for several years. Especially, the interpolation techniques for super resolution televisions become more and more important since the most video programs are only with high definition. The linear-based interpolation algorithms bring out the jaggy noise conspicuously. Recently, the new edge-directed interpolation (NEDI) is proposed to improve the accuracy with one-fold training size for predicting parameters. In this paper, an image interpolation based on Gaussian regularized regression with cross-based window (GRR-CW) approach is proposed. The GRR-CW contains spatial confidence consideration and cross-based window generation to lead the prediction more reliable. In experimental results, we prove that the proposed GRR-CW can achieve higher image quality in PSNR and SSIM performances than the traditional linear-based and NEDI-based algorithms.
UR - https://www.scopus.com/pages/publications/84962162296
UR - https://www.scopus.com/pages/publications/84962162296#tab=citedBy
U2 - 10.1109/TENCON.2015.7372960
DO - 10.1109/TENCON.2015.7372960
M3 - Conference contribution
AN - SCOPUS:84962162296
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
BT - TENCON 2015 - 2015 IEEE Region 10 Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th IEEE Region 10 Conference, TENCON 2015
Y2 - 1 November 2015 through 4 November 2015
ER -