No-Reference Quality Assessment of an Image Resizing Algorithms | Zendy

David Asatryan | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

No-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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research