TY - JOUR
T1 - No-Reference Physics-Based Quality Assessment of Polarization Images and Its Application to Demosaicking
AU - Li, Ning
AU - Teurnier, Benjamin Le
AU - Boffety, Matthieu
AU - Goudail, Francois
AU - Zhao, Yongqiang
AU - Pan, Quan
N1 - Publisher Copyright:
© 1992-2012 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - image demosaicking
KW - no-reference quality assessment
KW - Polarization imaging
UR - http://www.scopus.com/inward/record.url?scp=85118593523&partnerID=8YFLogxK
U2 - 10.1109/TIP.2021.3122085
DO - 10.1109/TIP.2021.3122085
M3 - 文章
C2 - 34705645
AN - SCOPUS:85118593523
SN - 1057-7149
VL - 30
SP - 8983
EP - 8998
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
ER -