Optimal decomposition level of discrete, stationary and dual tree complex wavelet transform for pixel based fusion of multi-focused images

Abstract

The fast development of digital image processing leads to the growth of feature extraction of images which leads to the development of Image fusion. Image fusion is defined as the 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 Direct Fusion and Multi resolution fusion. In Direct 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 resolution fusion uses transform for representing the source image at multi scale. The most common widely used transform for image fusion at multi scale is Wavelet Transform. This paper describes the optimal level of decomposition of discrete wavelet transform required for better pixel based fusion of multi focused images in terms of root mean square error, Peak Signal to Noise Ratio, Quality Index and Image fidelity.