TY - JOUR
T1 - Application of shift-and-add algorithms for imaging objects within biological media
AU - Aizert, Avishai
AU - Moshe, Tomer
AU - Abookasis, David
N1 - Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - The Shift-and-Add (SAA) technique is a simple mathematical operation developed to reconstruct, at high spatial resolution, atmospherically degraded solar images obtained from stellar speckle interferometry systems. This method shifts and assembles individual degraded short-exposure images into a single average image with significantly improved contrast and detail. Since the inhomogeneous refractive indices of biological tissue causes light scattering similar to that induced by optical turbulence in the atmospheric layers, we assume that SAA methods can be successfully implemented to reconstruct the image of an object within a scattering biological medium. To test this hypothesis, five SAA algorithms were evaluated for reconstructing images acquired from multiple viewpoints. After successfully retrieving the hidden object's shape, quantitative image quality metrics were derived, enabling comparison of imaging error across a spectrum of layer thicknesses, demonstrating the relative efficacy of each SAA algorithm for biological imaging.
AB - The Shift-and-Add (SAA) technique is a simple mathematical operation developed to reconstruct, at high spatial resolution, atmospherically degraded solar images obtained from stellar speckle interferometry systems. This method shifts and assembles individual degraded short-exposure images into a single average image with significantly improved contrast and detail. Since the inhomogeneous refractive indices of biological tissue causes light scattering similar to that induced by optical turbulence in the atmospheric layers, we assume that SAA methods can be successfully implemented to reconstruct the image of an object within a scattering biological medium. To test this hypothesis, five SAA algorithms were evaluated for reconstructing images acquired from multiple viewpoints. After successfully retrieving the hidden object's shape, quantitative image quality metrics were derived, enabling comparison of imaging error across a spectrum of layer thicknesses, demonstrating the relative efficacy of each SAA algorithm for biological imaging.
KW - Image quality assessment
KW - Image reconstruction techniques
KW - Imaging through scattering media
KW - Medical and biological imaging
KW - Multiple imaging
UR - http://www.scopus.com/inward/record.url?scp=84983428990&partnerID=8YFLogxK
U2 - 10.1016/j.optcom.2016.08.032
DO - 10.1016/j.optcom.2016.08.032
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AN - SCOPUS:84983428990
SN - 0030-4018
VL - 382
SP - 485
EP - 494
JO - Optics Communications
JF - Optics Communications
ER -