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
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;
Conference_Titel :
Information Fusion, 2005 8th International Conference on
Print_ISBN :
0-7803-9286-8
DOI :
10.1109/ICIF.2005.1591892