• DocumentCode
    3222169
  • Title

    Multi-frame image fusion using the expectation-maximization algorithm

  • Author

    Yang, Jinzhong ; Blum, Rick S.

  • Author_Institution
    ECE Dept., Lehigh Univ., Bethlehem, PA, USA
  • Volume
    1
  • fYear
    2005
  • fDate
    25-28 July 2005
  • Abstract
    A multi-frame image fusion scheme is proposed to fuse visual and thermal images for night vision applications. While many previous image fusion approaches perform the fusion on a frame-by-frame basis, this method considers optimum use of neighboring frames to incorporate temporal as well as sensor fusion. This fusion scheme is based on a statistical image formation model. The multiple sensor image frames are described as the true scene corrupted by additive non-Gaussian distortion. The expectation-maximization (EM) algorithm is used to estimate the parameters in the model and to produce the final fused result. The experimental results showed that the EM-based multi-frame image fusion scheme has significant advantage in terms of sensor noise reduction.
  • Keywords
    computer vision; expectation-maximisation algorithm; image processing; night vision; parameter estimation; sensor fusion; additive nonGaussian distortion; expectation-maximization algorithm; multiframe image fusion scheme; night vision application; parameter estimation; sensor fusion; sensor noise reduction; statistical image formation model; thermal image; Expectation-maximization algorithms; Fuses; Image fusion; Image sensors; Layout; Night vision; Noise reduction; Parameter estimation; Sensor fusion; Sensor phenomena and characterization; EM algorithm; Multi-frame image fusion; image formation model; night vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2005 8th International Conference on
  • Print_ISBN
    0-7803-9286-8
  • Type

    conf

  • DOI
    10.1109/ICIF.2005.1591892
  • Filename
    1591892