No-Reference Physics-Based Quality Assessment of Polarization Images and Its Application to Demosaicking

Ning Li, Benjamin Le Teurnier, Matthieu Boffety, Francois Goudail, Yongqiang Zhao, Quan Pan

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Assessing the quality of polarization images is of significance for recovering reliable polarization information. Widely used quality assessment methods including peak signal-to-noise ratio and structural similarity index require reference data that is usually not available in practice. We introduce a simple and effective physics-based quality assessment method for polarization images that does not require any reference. This metric, based on the self-consistency of redundant linear polarization measurements, can thus be used to evaluate the quality of polarization images degraded by noise, misalignment, or demosaicking errors even in the absence of ground-truth. Based on this new metric, we propose a novel processing algorithm that significantly improves demosaicking of division-of-focal-plane polarization images by enabling efficient fusion between demosaicking algorithms and edge-preserving image filtering. Experimental results obtained on public databases and homemade polarization images show the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)8983-8998
Number of pages16
JournalIEEE Transactions on Image Processing
Volume30
DOIs
StatePublished - 2021

Keywords

  • image demosaicking
  • no-reference quality assessment
  • Polarization imaging

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