An Improved Fusion Technique for IR and VIS Image using LWT and PCA

Image fusion techniques are divided into two broad categories: spatial domain and transform domain. Principal component analysis (PCA) is a spatial domain technique which is computationally simpler and reduces redundant information but has the demerit of spectral degradation. Lifting wavelet transform (LWT) is a transform domain technique which has an adaptive design and demands less memory. In this paper, a new hybrid fusion algorithm has been introduced which combines the LWT and PCA in a parallel manner. These two fusion methods are applied on Infrared and Visible images. The hybrid method is then compared with conventional fusion techniques like PCA, LWT and DWT. It has been shown that the proposed method outperforms conventional methods. The results are analyzed using performance parameters standard deviation, average value, the average difference, and normalized cross-correlation.