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Multi-band à trous wavelet transform for multisensor image fusion
2010 Edition, Volume 5, October 1, 2010 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

À trous wavelet transform is less spatial information distortion and without decimation in fusing multisensor images at same degree. Therefore, the image fused by à trous wavelet transform can get better performance than...

Objectively Optimised Multisensor Image Fusion
2006 Edition, July 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

A plethora of image fusion algorithms have been proposed recently, yet what are optimal fusion parameters that should be used for any multi-sensor dataset cannot be defined a priori. They could be learned by evaluating all available fusion...

Multisensor image fusion algorithm using nonseparable wavelet frame transform
2005 Edition, Volume 16, December 1, 2005 - China Aerospace Science and Industry Corporation (CASIC)

A multisensor image fusion algorithm is described using 2-dimensional nonseparable wavelet frame (NWF) transform. The source multisensor images are first decomposed by the NWF transform. Then, the NWF transform coefficients of...

Multisensor Image Fusion and Enhancement in Spectral Total Variation Domain
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Most existing image fusion methods assume that at least one input image contains high-quality information at any place of an observed scene. Thus, these fusion methods will fail if every input image is degraded. To address this issue, this study innovatively...

Multisensor image fusion based on a fuzzy neural network
2010 Edition, Volume 4, October 1, 2010 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Multisensor image fusion has its effective utilization for surveillance. In this paper, we utilize a fuzzy neural network approach to merge images from different sensors, in order to enhance visualization for surveillance. With the help of...

Multisensor image fusion using fuzzy logic for surveillance systems
2010 Edition, Volume 2, August 1, 2010 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Multisensor image fusion has its effective utilization for surveillance. In this paper, we utilize a fuzzy logic approach to fuse images from different sensors, in order to enhance visualization for surveillance. With the help of fuzzy if-then rules...

Multisensor image fusion by using discrete multiwavelet transform
2004 Edition, Volume 7, January 1, 2004 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We discuss the application of the discrete multiwavelet transform (DMWT) to multisensor image fusion processing. Multiwavelets are extension from scalar wavelets, and have several advantages in comparison with scalar wavelets. Multiwavelet analysis can...

Multiscale versus multiresolution analysis for multisensor image fusion
1998 Edition, September 1, 1998 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper, We propose a multisensor image fusion method based on the multiscale decomposition. In this representation, the redundant wavelet transform is performed on input images to emphasise the dominant details present at each scale. A...

A Framework for multisensor image fusion using graphics hardware
2008 Edition, June 1, 2008 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This paper presents a framework for pixel-level multisensor image fusion algorithm using graphics hardware. When it comes to the fusion technology of recent times, not only its visibility through information maximization which is brought about by the...

A multisensor image fusion algorithm based on PCNN
2004 Edition, Volume 4, January 1, 2004 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Based on the principle of pulse-coupled neural network (PCNN), a novel algorithm for multisensor image fusion is presented. Firstly a contrast pyramid decomposition of source images is performed, and then the contrast pyramids are used as the input...

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