Image fusion is the process of combining two
or more images of the same scene to form the fused image
retaining important features from each image with
extended information content. There are two approaches to
image fusion, namely Spatial Fusion and Transform fusion.
Transform fusion uses transform for representing the
source image at multi scale. Due to the compactness,
orthogonality and directional information, the Discrete
Wavelet Transforms and its un-decimated version are used
for image fusion. These transforms can be implemented
using perfect reconstruction Finite Impulse Response filter
banks which are either symmetric or orthogonal. To design
filters to have both symmetric and orthogonal properties,
the number of filters is increased to generate M-band
transform. Double density Discrete Wavelet Transform is
an example of M-band DWT and consists of one scaling
and two wavelet filters. In this paper, an approach for
DDWT based image fusion is designed using statistical
property of wavelet filters in representing the sharpness
and its performance is measured in terms of Root Mean
Square Error, Peak to Signal Noise Ratio.
Jyoti Pujar : Dept. of Electronics& Telecommunication
Rajarshi Shahu College of Engineeing, Pune-33
R R Itkarkar : Dept. of Electronics& Telecommunication
Rajarshi Shahu College of Engineeing, Pune-33
Image Fusion
Discrete Wavelet Transform
(DWT)
Finite Impulse Response Filter
M-Band Transform
and Double Density Discrete Wavelet Transform (DDWT)
This paper presents an efficient method of multi focus
image fusion using DDWT. This method evaluates the
sharpness measure in wavelet domain using distribution
of the wavelet coefficients. A study is also carried out to
find the optimum level of decomposition of DDWT for
this statistic based fusion of multi focused images in
terms of various performance measures. The results
show that third or fourth level of decomposition of
DDWT provides computationally efficient and better
qualitative and quantitative results. Hence using this
fusion method one can enhance the image with high
geometric resolution.
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