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Title
Abstract
Introduction and Background
Materials and Methods
Preliminary Results
Dataset
Results and Discussions
Objective Image Interpolation Quality Assessment
Subjective Image Interpolation Quality Assessment
Conclusions
References
All Topics
Computer Science
Computer Graphics

Normalized Weighting Schemes for Image Interpolation Algorithms

Profile image of Olivier Rukundo, Ph.D.Olivier Rukundo, Ph.D.

2023, Applied Sciences

https://doi.org/10.3390/APP13031741
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16 pages

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Abstract

Image interpolation algorithms pervade many modern image processing and analysis applications. However, when their weighting schemes inefficiently generate very unrealistic estimates, they may negatively affect the performance of the end-user applications. Therefore, in this work, the author introduced four weighting schemes based on some geometric shapes for digital image interpolation operations. Moreover, the quantity used to express the extent of each shape’s weight was the normalized area, especially when the sums of areas exceeded a unit square size. The introduced four weighting schemes are based on the minimum side-based diameter (MD) of a regular tetragon, hypotenuse-based radius (HR), the virtual pixel length-based height for the area of the triangle (AT), and the virtual pixel length for hypotenuse-based radius for the area of the circle (AC). At the smaller scaling ratio, the image interpolation algorithm based on the HR scheme scored the highest at 66.6% among non-traditional image interpolation algorithms presented. However, at the higher scaling ratio, the AC scheme-based image interpolation algorithm scored the highest at 66.6% among non-traditional algorithms presented, and, here, its image interpolation quality was generally superior or comparable to the quality of images interpolated by both non-traditional and traditional algorithms.

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