Hierarchical adaptive regularisation method for depth extraction from planar recording of 3D-integral images

Silvia Manolache, Malcolm McCormick, Sun-Yuan Kung

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The paper presents a novel algorithm for object space reconstruction from the planar (2D) recorded data set of a 3D-integral image. The integral imaging system is described and the associated point spread function is given. The space data extraction is formulated as an inverse problem, which proves ill-conditioned, and tackled by using a hierarchical multiresolution strategy and imposing additional conditions to the sought solution. The hierarchisation strategy and the two-phase adaptive constrained 3D-reconstruction algorithm based on the use of two sigmoid functions are presented. Finally, illustrative simulation results are given.

Original languageEnglish (US)
Pages (from-to)1433-1436
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
DOIs
StatePublished - Jan 1 2001

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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