Back to articles
Regular Articles
Volume: 63 | Article ID: jist0746
Image
Validation of Modulation Transfer Functions and Noise Power Spectra from Natural Scenes
  DOI :  10.2352/J.ImagingSci.Technol.2019.63.6.060406  Published OnlineNovember 2019
Abstract
Abstract

The Modulation Transfer Function (MTF) and the Noise Power Spectrum (NPS) characterize imaging system sharpness/resolution and noise, respectively. Both measures are based on linear system theory. However, they are applied routinely to scene-dependent systems applying non-linear, content-aware image signal processing. For such systems, MTFs/NPSs are derived inaccurately from traditional test charts containing edges, sinusoids, noise or uniform luminance signals, which are unrepresentative of natural scene signals. The dead leaves test chart delivers improved measurements from scene-dependent systems but still has its limitations. In this article, the authors validate novel scene-and-process-dependent MTF (SPD-MTF) and NPS (SPD-NPS) measures that characterize (i) system performance concerning one scene, (ii) average real-world performance concerning many scenes or (iii) the level of system scene dependency. The authors also derive novel SPD-NPS and SPD-MTF measures using the dead leaves chart. They demonstrate that the proposed measures are robust and preferable for scene-dependent systems to current measures.

Subject Areas :
Views 51
Downloads 3
 articleview.views 51
 articleview.downloads 3
  Cite this article 

Edward W. S. Fry, Sophie Triantaphillidou, Robin B. Jenkin, John R. Jarvis, Ralph E. Jacobson, "Validation of Modulation Transfer Functions and Noise Power Spectra from Natural Scenesin Journal of Imaging Science and Technology,  2019,  pp 060406-1 - 060406-11,  https://doi.org/10.2352/J.ImagingSci.Technol.2019.63.6.060406

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2019
  Article timeline 
  • received July 2019
  • accepted October 2019
  • PublishedNovember 2019

Preprint submitted to:
  Login or subscribe to view the content