High resolution depth image recovery algorithm based on the modeling of the sum of an average distance image and a surface image

Kazunori Uruma, Katsumi Konishi, Tomohiro Takahashi, Toshihiro Furukawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper proposes a new depth image recovery algorithm which recovers a high resolution depth image using RGB color image from a very low resolution depth image. In order to achieve a high recovery performance, this paper represents the high resolution depth image as the sum of an average distance image and a surface image. Experimental examples show that the proposed algorithm achieves a high resolution depth recovery from a very low resolution depth image effectively.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages2836-2840
Number of pages5
ISBN (Electronic)9781467399616
DOIs
Publication statusPublished - 3 Aug 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period25/09/1628/09/16

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Keywords

  • Depth image recovery
  • Image segmentation
  • Super resolution

Cite this

Uruma, K., Konishi, K., Takahashi, T., & Furukawa, T. (2016). High resolution depth image recovery algorithm based on the modeling of the sum of an average distance image and a surface image. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (pp. 2836-2840). [7532877] (Proceedings - International Conference on Image Processing, ICIP; Vol. 2016-August). IEEE Computer Society. https://doi.org/10.1109/ICIP.2016.7532877