Sensor Fused Night Vision : Assessing Image Quality in the Lab and in the Field

Generating real-time fused combinations of VNIR, SWIR and LWIR imagery enhances situational awareness, task performance, and overall image quality. However, no quantitative means to link image quality metrics with task performance exist for fused imaging, the way it does for single modality imaging. We illustrate how fused image quality is affected by multiple dimensions, including scene illumination, reflectance contrast, thermal contrast, sensor resolution, noise-limited resolution, local adaptive gain & contrast enhancement, noise cleaning, and fusion methodology. Task performance has also been assessed in two field collection campaigns, and multiple human performance tests in the lab using field data. Though image fusion clearly improves subjective image quality, a means to predict task performance improvement is still lacking

[1]  J C Leachtenauer,et al.  General Image-Quality Equation: GIQE. , 1997, Applied optics.

[2]  Lucien M. Biberman Electro-optical imaging : system performance and modeling , 2001 .

[3]  Joseph P. Racamato,et al.  Solid-State Color Night Vision: Fusion of Low-Light Visible and Thermal Infrared Imagery , 1998 .

[4]  Allen M. Waxman,et al.  Color Night Vision: Opponent Processing in the Fusion of Visible and IR Imagery , 1997, Neural Networks.

[5]  Alexander Toet,et al.  Fusion of visible and thermal imagery improves situational awareness , 1997 .

[6]  Michael Kelley,et al.  National imagery interpretation rating system and the probabilities of detection, recognition, and identification , 1997 .

[7]  R. Biehl,et al.  Realtime image fusion and target learning & detection on a laptop attached processor , 2005, 2005 7th International Conference on Information Fusion.

[8]  Allen M. Waxman,et al.  Field evaluations of dual-band fusion for color night vision , 1999, Defense, Security, and Sensing.

[9]  Alexander Toet,et al.  New false color mapping for image fusion , 1996 .

[10]  Peter J. Burt,et al.  Enhanced image capture through fusion , 1993, 1993 (4th) International Conference on Computer Vision.

[11]  Alexander Toet,et al.  Merging thermal and visual images by a contrast pyramid , 1989 .

[12]  Alexander Toet,et al.  Fusion of visible and thermal imagery improves situational awareness , 1997, Defense, Security, and Sensing.

[13]  J Irvine,et al.  General image-quality equation for infrared imagery. , 2000, Applied optics.

[14]  Philip Perconti,et al.  Part task investigation of multispectral image fusion using gray scale and synthetic color night vision sensor imagery for helicopter pilotage , 1997 .

[15]  Daniel Grau,et al.  Real-time image fusion and target learning and detection on a laptop attached processor , 2005, SPIE Defense + Commercial Sensing.