Adaptive image interpolation technique based on cubic trigonometric B‐spline representation. Issue 5 (1st May 2018)

• Record Type: Journal Article
• Authors: Abbas, Samreen; Irshad, Misbah; Hussain, Malik Zawwar
• Is Part Of: IET image processing. Volume 12:Issue 5(2018)
• Page Start: 769
• Page End: 777
• Publication Date: 2018-05-01
• Subjects: interpolation -- splines (mathematics) -- image representation -- genetic algorithms; adaptive image interpolation technique -- cubic trigonometric B‐spline representation -- soft computing technique -- genetic algorithm -- sum square error minimisation -- two‐dimensional digital image interpolation -- image quality metrics peak signal‐to‐noise ratio -- multiscale structure similarity index -- feature similarity index; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2016.0393
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : A cubic trigonometric B‐spline representation with two parameters is constructed in this work. A soft computing technique, genetic algorithm, is used to find the optimal value of the parameters in the description of B‐spline so that the sum square error is minimised. The newly constructed B‐spline is then utilised to interpolate two‐dimensional digital images. The image quality metrics peak signal‐to‐noise ratio, structure SIMilarity index, multi‐scale structure SIMilarity index and feature SIMilarity index are used to investigate the quality of interpolated digital images. Comparison with already existing image interpolation schemes leads to the conclusion that the proposed image interpolation technique is found to be a valuable scheme for the problems related to digital image interpolation.