Image Processing Reference
In-Depth Information
Fig. 2.2
Illustration of wavelet-based image fusion
then recovered via an inverse discrete wavelet transform (IDWT) to generate the final
image. The schematic of the generalized DWT-based fusion techniques is shown in
Fig. 2.2 . The pyramidal representations of the input images are subjected to the fusion
rule specified by the technique. This process generates the pyramid representing the
decomposed fused image. The final image is obtained by an appropriate inverse
As stated earlier in this monograph, the key step lies in choosing an appropriate
strategy to combine the coefficients, i.e., fusion rule. In [172, 174], the fusion rule
has been defined to select the maximum of the corresponding coefficients of the
ratio pyramid of input images, while the fusion rule that selects the maximum across
discrete wavelet coefficients of the input images has been proposed in [104]. Math-
ematically, the general wavelet-based image fusion can be represented by Eq. ( 2.2 ).
= W 1 F W (
I 2 ),... ,
I 1 ), W (
W , W 1 are the forward and inverse wavelet trans-
formoperators, respectively. Wavelets have probably been themost successful family
of fusion techniques. Wavelet-based fusion techniques have been implemented for
various other application areas. Wen and Chen have demonstrated several applica-
tions of DWT-based fusion for forensic science [188]. Another application of wavelet
decomposition for fusion of multi-focus images using the log-Gabor wavelets has
been described by Redondo et al. [151]. The wavelet-based fusion techniques have
also been proved to be useful for fusion of medical images. Performance of vari-
ous multi-resolution techniques for fusion of retinal images has been analyzed in
[96, 97]. In [86], wavelets have been shown to be useful for fusion of CT and MRI
Let us now take a brief look at some of the fusion techniques based on the variants
of wavelets. A region-based fusion technique that generates a feature map through
segmentation of the features of input images using a dual-tree complex wavelet
is the fusion rule, and
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