Open Access   Article Go Back

Computational Time Complexity of Image Interpolation Algorithms

P.S. Parsania1 , P. V. Virparia2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 491-496, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.491496

Online published on Jul 31, 2018

Copyright © P.S. Parsania, P. V. Virparia . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: P.S. Parsania, P. V. Virparia, “Computational Time Complexity of Image Interpolation Algorithms,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.491-496, 2018.

MLA Style Citation: P.S. Parsania, P. V. Virparia "Computational Time Complexity of Image Interpolation Algorithms." International Journal of Computer Sciences and Engineering 6.7 (2018): 491-496.

APA Style Citation: P.S. Parsania, P. V. Virparia, (2018). Computational Time Complexity of Image Interpolation Algorithms. International Journal of Computer Sciences and Engineering, 6(7), 491-496.

BibTex Style Citation:
@article{Parsania_2018,
author = {P.S. Parsania, P. V. Virparia},
title = {Computational Time Complexity of Image Interpolation Algorithms},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {491-496},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2463},
doi = {https://doi.org/10.26438/ijcse/v6i7.491496}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.491496}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2463
TI - Computational Time Complexity of Image Interpolation Algorithms
T2 - International Journal of Computer Sciences and Engineering
AU - P.S. Parsania, P. V. Virparia
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 491-496
IS - 7
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
519 381 downloads 280 downloads
  
  
           

Abstract

Image Interpolation is an important operation in many image processing software and applications. It is a process of enlarging or reducing the image size. To resize an image, every pixel in new image is calculated using the values of the pixels in old image. There are many algorithms available for determining new value of the pixel, most of which involve some form of interpolation among the nearest pixels in the old image. After interpolating new values for pixel, it is important to preserve the image quality. As a result of digital image operations, various methods suffer from different edge-related visual artifacts such as aliasing, edge blurring, and jaggies effect. For our study we have used Nearest-neighbor, Bilinear, Bicubic, Cubic B-spline, Catmull-Rom, Lanczos of order two and Lanczos of order three image interpolation algorithms. In this paper, an attempt is made to evaluate different image interpolation algorithms to compare time performance on Intel Core i3, i5 and i7 processors supported with different hardware configuration. The result shows that more time is required to compute the larger image. However, the time can be minimized using higher end hardware configuration.

Key-Words / Index Term

Interpolation, Computational Complexity, adaptive, non-adaptive, image quality, resize, scaling

References

[1] P. Bhatt, S. Patel, A. Shah, S. Patel, “Image Enhancement Using Various Interpolation Methods” IRACST - International Journal of Computer Science and Information Technology & Security (IJCSITS), Vol. 2, No.4, pp.799-803, 2012.
[2] D. Doma, “Comparison of Different Image Interpolation Algorithms”, West Virginia University Libraries, 2008.
[3] J. Titus, S. Geroge, “A Comparison Study On Different Interpolation Methods Based On Satellite Images”, International Journal of Engineering Research & Technology, Vol. 2, Issue 6, pp. 82-85 2013.
[4] P. S. Parsania, P. V. Virparia, “Image Quality Comparison using PSNR and UIQI for Image Interpolation Algorithms”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 12, pp. 21679-21687, 2016.
[5] K. Shah, J. Pandya, S. Vahora, “A Survey On Super Resolution Image Reconstruction Techniques”, International Journal of Engineering Research & Technology, Vol. 2, No. 4, pp. 1897-1901, 2013.
[6] G. Kaur, J. Kaur, “A Comparative Study of Image Demosaicing”, International Journal of Computer Sciences and Engineering, Vol. 3, Issue. 7, pp. 98-102, 2015.
[7] S. Fadnavis, “Image Interpolation Techniques in Digital Image Processing: An Overview”, International Journal of Engineering Research and Applications, Vol,. 4, No. 10, pp.70-73, 2015.
[8] A. Sinha, M. kumar, A. Jaiswal, R. Saxena, “Performance Analysis of High Resolution Images Using Interpolation Techniques in Multimedia Communication System”, Signal & Image Processing: An International Journal, Vol. 5, No. 2, pp. 39-49, 2014.
[9] A. Prajapati, S. Naik, S. Mehta, “Evaluation of Different Image Interpolation Algorithms”, International Journal of Computer Applications, Vol. 58, Issue. 1, pp. 6-12, 2012.
[10] T. Wu, B. Bai, P. Wang, “Parallel Catmull-Rom Spline Interpolation Algorithm for Image Zooming Based on CUDA”, International Journal of Applied Mathematics & Information Science, Vol. 7, No. 2, pp. 533-537, 2013.
[11] W. Burger, M. J. Burge, “Digital image processing: an algorithmic introduction using Java”, 1st ed., Springer, India, pp. 400-401, 2009.
[12] D. Han, “Comparison of Commonly Used Image Interpolation Methods”, In the Proceedings of 2nd International Conference on Computer Science and Electronics Engineering, France, pp.1556-1559, 2013.
[13] S. Singh, T. Gulati, “Upscaling Capsule Endoscopic Low Resolution Images”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, Issue. 5, pp. 40-46, 2014.
[14] C. Suresh, S. Singh, R. Saini, A. K. Saini, “A Comparative Analysis of Image Scaling Algorithms”, International Journal of Image, Graphics and Signal Processing, Vol. 5, Issue. 4, pp - 55-62, 2013.
[15] P. S. Parsania, P. V. Virparia, “Performance Analysis of Image Scaling Algorithms”, International Journal on Recent and Innovation Trends in Computing and Communication, vol. 4, Issue 6, pp. 521-526, 2016.