Super Resolution for Smartphones

Seiichi Gohshi, Sakae Inoue, Isao Masuda, Takashi Ichinose, Yoshika Tatsumi


Smartphones were developed as an advanced communication tool. Currently they are used in various applications. The display is one of the most important features in smartphones. Compared with television (TV) and cinema screens the display size of a smartphone is small. However, TV and film content is commonly enjoyed on smartphone screens. Currently, the smartphone display is one of the most used displays for various kinds of content. In the past it was thought that it would be difficult to recognize the resolution differences on small displays. However, this is no longer the case. The resolution of smartphones have been steadily improving, and high-definition television (HDTV) (1,920×1,080 pixels) viewing resolution support is common. Signal processing is another way to improve resolution. Super resolution (SR) has become an interesting research field and is applied to images and videos. SR is a technology for improving display resolution. Consequently, SR is mainly studied for application to TV screens and computer displays. SR technology algorithms are complex and a heavy load for a smartphone’s central or graphics processing unit (CPU/GPU). It is very difficult to apply SR for real-time videos on smartphones. Consequently, there have been no reports in SR for smartphones. This paper proposes a method for implementing real-time SR in smartphones. This method works for real-time videos on a smartphone GPU with the developed software.


  1. (2009). Toshiba press release.
  2. Candes, E. J. and Fernandez-Granda, C. (2014). Towards a mathematical theory of super resolution. Communications on Pure and Applied Mathematics, 67.6:906- 956.
  3. Dong, C., Loy, C. C., He, K., and Tang, X. (2014). Learning a deep convolutional network for image superresolution. Computer Vision-ECCV, pages 184-199.
  4. Elad, M. and Feuer, A. (1996). Super-resolution of continuous image sequence. IEEE Trans. on Pattern Analysis and Machine Intelligence.
  5. Farsiu, S., Robinson, M., Elad, M., and Milanfar, P. (2004). Fast and robust multi frame super resolution. IEEE Transactions on Image Processing, 13(10):1327-1344.
  6. Glasner, D., Bagon, S., , and Irani, M. (Oct. 2009). International conference on computer vision (iccv). SuperResolution from a Single Image.
  7. Katsaggelos, A., Molina, R., and Mateos, J. (2010). Super Resolution of Images and Video: Synthesis Lectures on Images, Video and Multimedia Processing. Morgan and Clayppo Publishers, La Vergne TN USA.
  8. Lee, J. S. (March 1980). Ieee trans. on pattern analysis and machine intelligence 2:165-168. Digital Image Enhancement and Noise Filtering by Use of Local Statistics.
  9. Matsumoto, N. and Ida, T. (2010). Reconstruction-based super-resolution using self-congruency around image edges. IEICE transactions on information and systems (in Japanese), J93-D(2)(2):118-126.
  10. Panda, S., Prasad, R., and Jena, G. (Sept. 2011). Pocs based super-resolution image reconstruction using an adaptive regularization parameter. IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No. 2, ISSN (Online), 1694-0814.
  11. Park, S. C., Park, M. K., and Kang, M. G. (2003). Super-resolution image reconstruction: A technical overview. IEEE Signal Processing Magazine, 1053- 5888/03:21-36.
  12. Pratt, W. (2001). Digital Image Processing (3rd Ed): New York. John Wiley and Sons.
  13. Schreiber, W. F. (1970). Wirephoto quality improvement by unsharp masking. J. Pattern Recognition, 2:111-121.
  14. Sun, J., Sun, J., Xu, Z., and Shum, H. (2008). Image superresolution using gradient profile prior. CVPR 2008, pages 1-8.
  15. van Eekeren, A. W. M., Schutte, K., and van Vliet, L. J. (2010). Multiframe super-resolution reconstruction of small moving objects. IEEE Transactions on Image Processing, 19(11):2901-2912.

Paper Citation

in Harvard Style

Gohshi S., Inoue S., Masuda I., Ichinose T. and Tatsumi Y. (2016). Super Resolution for Smartphones . In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016) ISBN 978-989-758-196-0, pages 106-112. DOI: 10.5220/0005991301060112

in Bibtex Style

author={Seiichi Gohshi and Sakae Inoue and Isao Masuda and Takashi Ichinose and Yoshika Tatsumi},
title={Super Resolution for Smartphones},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016)},

in EndNote Style

JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016)
TI - Super Resolution for Smartphones
SN - 978-989-758-196-0
AU - Gohshi S.
AU - Inoue S.
AU - Masuda I.
AU - Ichinose T.
AU - Tatsumi Y.
PY - 2016
SP - 106
EP - 112
DO - 10.5220/0005991301060112