Area level fusion of Multi-focused Images using Double Density DWT and DTCWT

Image fusion is a process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely spatial fusion and multi scale transform fusion. In spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the composite image at that location. Multi scale transform fusion usestransform for representing the source image at multi scale. The most common widely used transform for image fusion at multi scale is Discrete Wavelet Transform (DWT) since it minimizes structural distortions. But, wavelet transform cannot provide efficient approximation for directional features of images which in turn affects the performance of DWT-based image fusion schemes. Many multi scale tools have been invented to boost image fusion performance by incorporating directional representation. These tools can be classified into two categories according to the domain where they are designed: Spatial-domain Multiscale Directional Transform (SMDT) and Frequency domain Multiscale Directional Transform (FMDT). In FMDT, the basis functions of each subband orient at a certain direction, overcoming the poor directionality of 2-D DWT. Representative work includes curvelets, contourlets, bandelets, directionlets, multiscale directional filter banks, and complex wavelets. The critically sampled DWT is not a shift-invariant discrete transform, but the Dual Tree Complex Wavelet Transform (DT-CWT) introduced by Kingsbury is approximately shift -invariant and provides directional analysis whereas the undecimated DWT (UDWT) is an exactly shift-invariant transform. When J scales are implemented, the UDWT is expansive by the factor J + 1. The Double-density Discrete Wavelet Transform (DDWT) proposed by Ivan W. Selesnick provides a compromise between the UDWT and the critically-sampled DWT. A Double-density DTCWT (DDT-CWT), also proposed by Ivan W. Selesnick is an over-complete DWT designed to simultaneously possess the good properties of the DDWT and the DTCWT. And there are three levels for image fusion amel pixel level, area level and region level. In this paper, it is proposed to implement area level fusion of multi focused images using Double Density DWT and DTCWPT and the performance is measured in terms of various performance measures like ischolar_main mean square error and peak signal to noise ratio.