[IPOL announce] new article: Reversibility Error of Image Interpolation Methods: Definition and Improvements

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2019/277/

Thibaud Briand,
Reversibility Error of Image Interpolation Methods: Definition and 
Improvements,
Image Processing On Line, 9 (2019), pp. 360–380.
https://doi.org/10.5201/ipol.2019.277


Abstract
There is no universal procedure in image processing for evaluating the 
quality and performance of an interpolation method. In this work, we 
introduce a new quantity: the reversibility error. For a given image, it 
measures the error after applying successively a homography close to the 
identity, a crop (removing boundary artifacts) and the inverse 
homography. An average over random homographies is made to remove the 
dependency on the homography. A more precise measurement discarding very 
high-frequency artifacts is obtained by clipping the spectrum of the 
difference. We also propose new fine-tuned interpolation methods that 
are based on the DFT zoom-in and pre-existing (or base) interpolation 
methods. The zoomed version of an interpolation method is obtained by 
applying it to the DFT zoom-in of the image. In the periodic plus smooth 
version of interpolation methods, the non-periodicity is handled by 
applying the zoomed version to the periodic component and a base 
interpolation method to the smooth component. In an experimental part, 
we show that the proposed fine-tuned methods have smaller reversibility 
errors than their base interpolation methods and that the error is 
mainly localized in a small high-frequency band. We recommend to use the 
periodic plus smooth versions of high order B-spline. It is more 
efficient and provides better results than trigonometric polynomial 
interpolation.