Resolution enhancement of PMD range maps

A. N. Rajagopalan, Arnav Bhavsar, Frank Wallhoff, Gerhard Rigoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

47 Scopus citations


Photonic mixer device (PMD) range cameras are becoming popular as an alternative to algorithmic 3D reconstruction but their main drawbacks are low-resolution (LR) and noise. Recently, some interesting works have stressed on resolution enhancement of PMD range data. These works use high-resolution (HR) CCD images or stereo pairs. But such a system requires complex setup and camera calibration. In contrast, we propose a super-resolution method through induced camera motion to create a HR range image from multiple LR range images. We follow a Bayesian framework by modeling the original HR range as a Markov random field (MRF). To handle discontinuities, we propose the use of an edge-adaptive MRF prior. Since such a prior renders the energy function non-convex, we minimize it by graduated non-convexity.

Original languageEnglish
Title of host publicationPattern Recognition - 30th DAGM Symposium, Proceedings
Number of pages10
StatePublished - 2008
Event30th DAGM Symposium on Pattern Recognition - Munich, Germany
Duration: 10 Jun 200813 Jun 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5096 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference30th DAGM Symposium on Pattern Recognition


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