Optimized depth of field methodology using annular liquid crystal modulator assisted by image processing

Naama Shukrun, Asi Solodar, Amir Aizen, Isaac August, Iftach Klapp, Yitzhak Yitzhaky, Ibrahim Abdulhalim

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

An optical-digital tunable depth of field (DOF) methodology is presented. The suggested methodology forms a fused image based on the sharpest similar depth regions from a set of source images taken with different phase masks. Each phase mask contains a different degree of DOF extension and is implemented by using an annular liquid crystal spatial light modulator, which consists of 16-ring electrodes positioned in the pupil plane. A detailed description of the optical setup and characterization of selected pupil phase masks as well as optimization of the binary phase mask for maximal DOF extension is presented. Experimental results are investigated both qualitatively and quantitatively. In addition, the algorithm's results are compared with those of some well-known fusion algorithms and proved its supremacy.

Original languageEnglish
Pages (from-to)3764-3772
Number of pages9
JournalApplied Optics
Volume56
Issue number13
DOIs
StatePublished - 1 May 2017

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Optimized depth of field methodology using annular liquid crystal modulator assisted by image processing'. Together they form a unique fingerprint.

Cite this