Literature DB >> 18286024

Fast phase-unwrapping algorithm based on a gray-scale mask and flood fill.

A Asundi, Z Wensen.   

Abstract

Phase-unwrapping algorithms, an active and interesting subject in recent years, are important in a great number of measurement applications. Active research is being undertaken to develop reliable and high-speed procedures. The current process uses a gray-scale mask and the flood-fill concept from image processing for phase unwrapping. The algorithm unwraps phase from an area with higher reliability to one with lower reliability. In addition to robustness, the speed of the algorithm proposed is much faster than conventional routines. The experimental results of different algorithms are compared by analysis of a tooth plaster and a photoelastic specimen.

Entities:  

Year:  1998        PMID: 18286024     DOI: 10.1364/ao.37.005416

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  3 in total

1.  SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging.

Authors:  Tanuj Misra; Alka Arora; Sudeep Marwaha; Viswanathan Chinnusamy; Atmakuri Ramakrishna Rao; Rajni Jain; Rabi Narayan Sahoo; Mrinmoy Ray; Sudhir Kumar; Dhandapani Raju; Ranjeet Ranjan Jha; Aditya Nigam; Swati Goel
Journal:  Plant Methods       Date:  2020-03-18       Impact factor: 4.993

2.  Center-environment feature models for materials image segmentation based on machine learning.

Authors:  Yuexing Han; Ruiqi Li; Shen Yang; Qiaochuan Chen; Bing Wang; Yi Liu
Journal:  Sci Rep       Date:  2022-07-28       Impact factor: 4.996

3.  Atrial fibrillation source area probability mapping using electrogram patterns of multipole catheters.

Authors:  Prasanth Ganesan; Elizabeth M Cherry; David T Huang; Arkady M Pertsov; Behnaz Ghoraani
Journal:  Biomed Eng Online       Date:  2020-05-05       Impact factor: 2.819

  3 in total

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