Correcting camera shake by incremental sparse approximation

Huaizhong Zhang, Ehab Essa, Xianghua Xie

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)

6 Citations (Scopus)

Abstract

In this paper, we present a graph based segmentation method that only requires a single point from user initialization. We incorporate a new image feature into the segmentation scheme. It is derived from a vector field that takes into account gradient vector interactions across the image domain, and has the simplicity of edge based features but also proves to be a useful region indication in two-level segmentation. Effective vector field diffusion is proposed to deal with excessive image noise. Based on a single user point we unravel the image and transfer the object segmentation into a height field segmentation in polar coordinates, which in effect imposes a star shape prior. The search of a minimum closed set on a node weighted, directed graph produces the segmentation result. Comparative analysis on real world images demonstrates promising performances of the proposed method in segmentation accuracy and its simplicity in user interaction.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Pages572-576
Number of pages5
DOIs
Publication statusE-pub ahead of print - 13 Feb 2014
EventIEEE 20th International Conference - Melbourne, Australia
Duration: 15 Sep 201318 Sep 2013

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

ConferenceIEEE 20th International Conference
CountryAustralia
CityMelbourne
Period15/09/1318/09/13

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  • Cite this

    Zhang, H., Essa, E., & Xie, X. (2014). Correcting camera shake by incremental sparse approximation. In 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings (pp. 572-576). (2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings). https://doi.org/10.1109/ICIP.2013.6738118