CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Image Registration using Combination of GPOF and Gradient Method for Image Super Resolution

by Niyanta Panchal, Ankit Prajapati, Bhailal Limbasiya
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 8
Year of Publication: 2014
Authors: Niyanta Panchal, Ankit Prajapati, Bhailal Limbasiya
10.5120/16818-6675

Niyanta Panchal, Ankit Prajapati, Bhailal Limbasiya . Image Registration using Combination of GPOF and Gradient Method for Image Super Resolution. International Journal of Computer Applications. 96, 8 ( June 2014), 30-35. DOI=10.5120/16818-6675

@article{ 10.5120/16818-6675,
author = { Niyanta Panchal, Ankit Prajapati, Bhailal Limbasiya },
title = { Image Registration using Combination of GPOF and Gradient Method for Image Super Resolution },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 8 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number8/16818-6675/ },
doi = { 10.5120/16818-6675 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:22:51.220797+05:30
%A Niyanta Panchal
%A Ankit Prajapati
%A Bhailal Limbasiya
%T Image Registration using Combination of GPOF and Gradient Method for Image Super Resolution
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 8
%P 30-35
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Super Resolution implementation using multi-frame super resolution has been an expensive topic in the literature. Multi-frame Super-Resolution is to generate the high-resolution image from multiple low-resolution images perspectives of a same scene. Most important part of multi-frame Super-resolution is Image Registration; that estimates the translation, rotation and scaling parameters and also aligns images. In this paper, they propose a combination of Gaussian Pyramid Optical Flow (GPOF) Registration method and Gradient method for constructing Super Resolution image. In the proposed approach, they focus on the movement model of the image registration GPOF, which reach the sub-pixel and allows for the large pixel motions, while keeping the size of image neighborhood relatively small. And apply Gradient method, which can accurately perform precise registration with the amount of image movement is small between the two images; it can get the one reconstructed image. They get the better results compares with the others registration methods. And lastly, they apply Discrete Wavelet Transform (DWT) image interpolation algorithm; they can get the high resolution image. Experiment results show that the HR image by their proposed method have much higher quality than other methods.

References
  1. S. C. Park, M. K. Park, and M. G. Kang, "Super-resolution image reconstruction: A technical review," IEEE Signal Processing Mag. , vol. 20, pp. 21–36, May 2003.
  2. S. Chaudhuri, Ed. , Super-Resolution Imaging. Norwell, MA: Kluwer, 2001.
  3. Lan Zhang; Hua Zhang; Simiao Zhang; YanbingXue, "Multi-frame image super-resolution reconstruction based on GPOF registration and L1-norm," Natural Computation (ICNC), 2010 Sixth International Conference on , vol. 7, no. , pp. 3601,3604, 10-12 Aug. 2010
  4. Sasatani, S. ; Xian-Hua Han; Yen-wei Chen, "Image registration using PCA and gradient method for super-resolution imaging," Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on , vol. , no. , pp. 631,634, 23-25 June 2010
  5. Ping-Sing Tsai, Tinku Acharya," Image Up-Sampling Using Discrete Wavelet Transform", 9th JCIS 2006, 8 to 11 October 2006.
  6. Simon Baker, Takeo Kanade, "Super-resolution optical flow", Technical Report CMU.
  7. Nan Zhao; Cuihua Li; Hua Shi; Chen Lin, "Multi-Frame Image Super-Resolution Based on Regularization Scheme," Control, Automation and Systems Engineering (CASE), 2011 International Conference on , vol. , no. , pp. 1,4, 30-31 July 2011
  8. S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust Multi-frame super resolution", IEEE Trans. Image Process. , vol. 13, no. 10, pp. 1327-1344, 2004.
  9. Chidananda Murthy, M. V. ; Yallapurmath, V. ; Kurian, M. Z. ; Guruprasad, H. S. , "Design and implementation of interpolation algorithms for image super resolution," Communication Systems, Networks & Digital Signal Processing (CSNDSP), 2012 8th International Symposium on, vol. , no. , pp. 1,6, 18-20 July 2012
  10. Vishal R. Jaiswal, Suhas H. Patil, Girish P. Potdar, ShrishailT. Patil," Multi-frame Image Super-Resolution-A Comparison",(IJCSE) International Journal On Computer Science and Engineering, Vol. 02, No. 09, 2010, ISSN 0975-3397
  11. Xuelong Li, Yanting Hu, Xinbo Gao, et. al, "A multi-frame image super-resolution method". IEEE Transactions on Signal Processing 90, pp. 405-414, 2010.
  12. Turgay Celik, Kai-Kuang Ma, "Fast Object-based Image Registration Using Principal Component Analysis for Super-resolution Imaging", 5th International Conference on Visual Information Engineering, pp. 705-710, 2008.
  13. Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity", IEEE Trans. Image Process. , vol. 13, no. 4, pp. 600-612, 2004.
  14. Yusra A. Y. Al-Najjar, Dr. Der Chen Soong," Comparison of Image Quality Assessment: PSNR, HVS, SSIM, UIQI ", International Journal of Scientific & Engineering Research, Volume 3, Issue 8, August-2012 1 ISSN 2229-5518
  15. R. Tsai, T. Huang,"Multi-frame image restoration and registration, in: Advances in Computer Vision and Image Processing, vol. 1, no. 2, JAI Press Inc. , Greenwich, CT, 1984, pp. 317–339.
  16. Nelson, K. ; Bhatti, A. ; Nahavandi, S. , "Performance Evaluation of Multi-Frame Super-Resolution Algorithms," Digital Image Computing Techniques and Applications (DICTA), 2012 International Conference on ,vol. , no. , pp. 1,8, 3-5 Dec. 2012
Index Terms

Computer Science
Information Sciences

Keywords

Super-Resolution Gaussian Pyramid Optical Flow Gradient method Discrete Wavelet Transform

Powered by PhDFocusTM