Proceedings Article | 29 November 2007
KEYWORDS: Image fusion, Wavelets, Image processing, Wavelet transforms, Image filtering, Distortion, Signal to noise ratio, Image sensors, Fusion energy, Medical imaging
Image fusion could process and utilize the source images, with complementing different image information, to
achieve the more objective and essential understanding of the identical object. Recently, image fusion has been
extensively applied in many fields such as medical imaging, micro photographic imaging, remote sensing, and computer
vision as well as robot.
There are various methods have been proposed in the past years, such as pyramid decomposition and wavelet
transform algorithm. As for wavelet transform algorithm, due to the virtue of its multi-resolution, wavelet
transform has been applied in image processing successfully. Another advantage of wavelet transform is that it can
be much more easily realized in hardware, because its data format is very simple, so it could save a lot of resources,
besides, to some extent, it can solve the real-time problem of huge-data image fusion. However, as the orthogonal
filter of wavelet transform doesn't have the characteristics of linear phase, the phase distortion will lead to the distortion
of the image edge. To make up for this shortcoming, the biorthogonal wavelet is introduced here. So, a novel image
fusion scheme based on biorthogonal wavelet decomposition is presented in this paper. As for the low-frequency
and high-frequency wavelet decomposition coefficients, the local-area-energy-weighted-coefficient fusion rule is
adopted and different thresholds of low-frequency and high-frequency are set. Based on biorthogonal wavelet
transform and traditional pyramid decomposition algorithm, an MMW image and a visible image are fused in the
experiment. Compared with the traditional pyramid decomposition, the fusion scheme based biorthogonal wavelet
is more capable to retain and pick up image information, and make up the distortion of image edge. So, it has a
wide application potential.
