Real-time global motion blur detection

Karl S. Ni, Zachary Z. Sun, Nadya T. Bliss

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

1 Scopus citations

Abstract

Most video exploitation algorithms operate on individual frames. To effect good results in such applications, the algorithms require good frames with which to work. However, videos may contain artifacts such as blur which inhibit the extraction of inherent and useful information. This paper proposes an algorithm that detects poor video frames induced by global motion blur. The proposed algorithm is divided into two steps: the first of which creates a single image blur metric, and the second of which adds temporal information. The blur metric is derived from a linear least squares fit to the log distribution of the highest subbands in a wavelet-based Haar filters. The second part of the algorithm correlates adjacent frames to boost performance. The ideas presented in this paper are low in complexity yet high in performance. Additionally, the proposed algorithm has been tested on natural video data as well as synthesized blur, and comparisons to state of the art show an advantage in using wavelet-based thresholding.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages3101-3104
Number of pages4
DOIs
StatePublished - Dec 1 2012
Externally publishedYes
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Publication series

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

Other

Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
CountryUnited States
CityLake Buena Vista, FL
Period9/30/1210/3/12

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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