Fast image fusion on foveated images
Thesis by:
Janosch Peters
Advisor:
Gudrun Klinker
Supervision by:
Patrick Maier
Due date: 2013/08/15
Abstract
The goal of this thesis is to combine images from an intesified CCD (EMCCD) camera and an long wave infrared (LWIR) camera. The fused image should contain all salient features of the individual modalities. As the fused image is thought as an replacement for legacy analogous night vision, the fusion algorithm should provide at least 25 frames per second. To achieve high performance the images are to be
foveated. A foveated image is an image which has been compressed by taking advantage of the perceptual properties of the human visual system, namely the decreasing resolution of the retina by increasing eccentricity. The thesis should elaborate how image fusion and foveation methods can be combined efficently while providing a good fused image.
Pictures
Upper left: Night vision camera
Upper right: Infrared camera
Lower left: DWT Maximum Coefficient fusion in all bands
Lower right: DWT Maximum Coefficient fusion in high frequency bands and coefficient averaging in approximation band
Resources
GPUDWT: Discrete Wavelet Transform accelerated on GPU
Literature
Addison, Paul S.:
The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance, Bristol
and Philadelphia : The Institute of Physics Publishing, 2002