Open AccessNo-Reference Quality Assessment of an Image Resizing Algorithms
Author(s) -
David Asatryan
Publication year - 2019
Publication title -
mathematical problems of computer science
Language(s) - English
Resource type - Journals
eISSN - 2738-2788
pISSN - 2579-2784
DOI - 10.51408/1963-0044
Subject(s) - interpolation (computer graphics) , image (mathematics) , resizing , image quality , computer science , artificial intelligence , weibull distribution , quality (philosophy) , algorithm , measure (data warehouse) , computer vision , image scaling , pattern recognition (psychology) , mathematics , image processing , statistics , data mining , philosophy , epistemology , european union , business , economic policy
In this paper, a No-Reference method is proposed for quality assessment of an image resizing methods based on interpolation algorithms. Quality refers to the image blur. To this end, it is proposed to use a previously developed measure based on a statistical assessment of the Weibull distribution shape parameter, adopted as a model for gradient magnitude of an image. The results of numerical experiments are presented that allow us to evaluate and compare the quality of various image resizing algorithms.