Resolution enhancement for fiber bundle imaging using maximum a posteriori estimation

Jianbo Shao, Wei Chen Liao, Rongguang Liang, Jacobus J Barnard

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

We propose a new framework to jointly improve spatial resolution and remove fixed structural patterns for coherent fiber bundle imaging systems, based on inverting a principled forward model. The forward model maps a high-resolution representation to multiple images modeling random probe motions. We then apply a point spread function to simulate low-resolution figure bundle image capture. Our forward model also uses a smoothing prior. We compute a maximum a posteriori (MAP) estimate of the high-resolution image from one or more low-resolution images using conjugate gradient descent. Unique aspects of our approach include (1) supporting a variety of possible applicable transformations; (2) applying principled forward modeling and MAP estimation to this domain. We test our method on data synthesized from the USAF target, data captured from a transmissive USAF target, and data from lens tissue. In the case of the USAF target and 16 low-resolution captures, spatial resolution is enhanced by a factor of 2.8.

Original languageEnglish (US)
Pages (from-to)1906-1909
Number of pages4
JournalOptics Letters
Volume43
Issue number8
DOIs
StatePublished - Apr 15 2018

Fingerprint

bundles
fibers
augmentation
spatial resolution
high resolution
image resolution
descent
point spread functions
smoothing
lenses
gradients
probes
estimates

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Cite this

Resolution enhancement for fiber bundle imaging using maximum a posteriori estimation. / Shao, Jianbo; Liao, Wei Chen; Liang, Rongguang; Barnard, Jacobus J.

In: Optics Letters, Vol. 43, No. 8, 15.04.2018, p. 1906-1909.

Research output: Contribution to journalArticle

@article{4679c06f12cd48c89140bbe914743f6e,
title = "Resolution enhancement for fiber bundle imaging using maximum a posteriori estimation",
abstract = "We propose a new framework to jointly improve spatial resolution and remove fixed structural patterns for coherent fiber bundle imaging systems, based on inverting a principled forward model. The forward model maps a high-resolution representation to multiple images modeling random probe motions. We then apply a point spread function to simulate low-resolution figure bundle image capture. Our forward model also uses a smoothing prior. We compute a maximum a posteriori (MAP) estimate of the high-resolution image from one or more low-resolution images using conjugate gradient descent. Unique aspects of our approach include (1) supporting a variety of possible applicable transformations; (2) applying principled forward modeling and MAP estimation to this domain. We test our method on data synthesized from the USAF target, data captured from a transmissive USAF target, and data from lens tissue. In the case of the USAF target and 16 low-resolution captures, spatial resolution is enhanced by a factor of 2.8.",
author = "Jianbo Shao and Liao, {Wei Chen} and Rongguang Liang and Barnard, {Jacobus J}",
year = "2018",
month = "4",
day = "15",
doi = "10.1364/OL.43.001906",
language = "English (US)",
volume = "43",
pages = "1906--1909",
journal = "Optics Letters",
issn = "0146-9592",
publisher = "The Optical Society",
number = "8",

}

TY - JOUR

T1 - Resolution enhancement for fiber bundle imaging using maximum a posteriori estimation

AU - Shao, Jianbo

AU - Liao, Wei Chen

AU - Liang, Rongguang

AU - Barnard, Jacobus J

PY - 2018/4/15

Y1 - 2018/4/15

N2 - We propose a new framework to jointly improve spatial resolution and remove fixed structural patterns for coherent fiber bundle imaging systems, based on inverting a principled forward model. The forward model maps a high-resolution representation to multiple images modeling random probe motions. We then apply a point spread function to simulate low-resolution figure bundle image capture. Our forward model also uses a smoothing prior. We compute a maximum a posteriori (MAP) estimate of the high-resolution image from one or more low-resolution images using conjugate gradient descent. Unique aspects of our approach include (1) supporting a variety of possible applicable transformations; (2) applying principled forward modeling and MAP estimation to this domain. We test our method on data synthesized from the USAF target, data captured from a transmissive USAF target, and data from lens tissue. In the case of the USAF target and 16 low-resolution captures, spatial resolution is enhanced by a factor of 2.8.

AB - We propose a new framework to jointly improve spatial resolution and remove fixed structural patterns for coherent fiber bundle imaging systems, based on inverting a principled forward model. The forward model maps a high-resolution representation to multiple images modeling random probe motions. We then apply a point spread function to simulate low-resolution figure bundle image capture. Our forward model also uses a smoothing prior. We compute a maximum a posteriori (MAP) estimate of the high-resolution image from one or more low-resolution images using conjugate gradient descent. Unique aspects of our approach include (1) supporting a variety of possible applicable transformations; (2) applying principled forward modeling and MAP estimation to this domain. We test our method on data synthesized from the USAF target, data captured from a transmissive USAF target, and data from lens tissue. In the case of the USAF target and 16 low-resolution captures, spatial resolution is enhanced by a factor of 2.8.

UR - http://www.scopus.com/inward/record.url?scp=85045558901&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85045558901&partnerID=8YFLogxK

U2 - 10.1364/OL.43.001906

DO - 10.1364/OL.43.001906

M3 - Article

AN - SCOPUS:85045558901

VL - 43

SP - 1906

EP - 1909

JO - Optics Letters

JF - Optics Letters

SN - 0146-9592

IS - 8

ER -