Computer Science > Graphics
[Submitted on 17 Nov 2020 (v1), last revised 31 Jan 2023 (this version, v6)]
Title:Normalized Weighting Schemes for Image Interpolation Algorithms
View PDFAbstract: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. And, the quantity used to express the extent of each shape 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. But, 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.
Submission history
From: Olivier Rukundo [view email][v1] Tue, 17 Nov 2020 10:47:50 UTC (595 KB)
[v2] Sun, 22 Nov 2020 17:57:40 UTC (597 KB)
[v3] Sun, 4 Sep 2022 13:46:44 UTC (471 KB)
[v4] Wed, 14 Sep 2022 22:21:48 UTC (903 KB)
[v5] Thu, 6 Oct 2022 18:18:09 UTC (957 KB)
[v6] Tue, 31 Jan 2023 14:31:46 UTC (998 KB)
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