Literature DB >> 29114993

Removal of jitter noise in 3D shape recovery from image focus by using Kalman filter.

Hoon-Seok Jang1, Mannan Saeed Muhammad2, Tae-Sun Choi1.   

Abstract

In regard to Shape from Focus, one critical factor impacting system application is mechanical vibration of the translational stage causing jitter noise along the optical axis. This noise is not detectable by simply observing the image. However, when focus measures are applied, inaccuracies in the depth occur. In this article, jitter noise and focus curves are modeled by Gaussian distribution and quadratic function, respectively. Then Kalman filter is designed and applied to eliminate this noise in the focus curves, as a post-processing step after the focus measure application. Experiments are implemented with simulated objects and real objects to show usefulness of proposed algorithm.
© 2017 Wiley Periodicals, Inc.

Keywords:  Kalman filter; Shape from Focus (SFF); jitter noise; shape retrieval

Year:  2017        PMID: 29114993     DOI: 10.1002/jemt.22966

Source DB:  PubMed          Journal:  Microsc Res Tech        ISSN: 1059-910X            Impact factor:   2.769


  2 in total

1.  Jitter Elimination in Shape Recovery by using Adaptive Neural Network Filter.

Authors:  Sung-An Lee; Hoon-Seok Jang; Byung-Geun Lee
Journal:  Sensors (Basel)       Date:  2019-06-05       Impact factor: 3.576

2.  Jitter noise modeling and its removal using recursive least squares in shape from focus systems.

Authors:  Husna Mutahira; Vladimir Shin; Unsang Park; Mannan Saeed Muhammad
Journal:  Sci Rep       Date:  2022-08-18       Impact factor: 4.996

  2 in total

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