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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.

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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 -

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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

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