Authors: Priya Ranjan Muduli; Umesh Chandra Pati
Addresses: Department of Electrical Engineering, Indian Institute of Technology, Kharagpur-721302, India ' Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela-769008, India
Abstract: Since last few decades, multi sensor image fusion has been an emerging field of research in remote sensing, medical imaging and variety of computer vision applications. The primary objective of image fusion lies in the formation of a perceptually enhanced image from several multi sensor images using an appropriate fusion rule. The discrete wavelet transform (DWT)-based image fusion techniques have been popular due to less redundancy, low computations and perfect reconstruction with short support filters. But, it suffers severely from lack of directionality, shift variance, oscillations and aliasing problems. These issues have been overcome by means of Q-shift dual-tree complex wavelet transform (DT-CWT)-based image fusion. In this paper, an improved DT-CWT-based image fusion technique has been proposed to compose a resultant image with better perceptual as well as quantitative image quality indices. A bilateral sharpness based weighting scheme has been implemented for the high frequency coefficients taking both gradient and its phase coherence in account. A normalised maximum gradient weighting scheme is implemented for low frequency wavelet components. The fusion results demonstrate that the proposed fusion technique is more effective and competitive in terms of entropy, total standard deviation, average gradient measure and edge intensity measure.
Keywords: bilateral sharpness criterion; discrete wavelet transform; DWT; dual-tree complex wavelet transform; DT-CWT; image fusion; phase congruency; multiresolution analysis; MRA; multi-sensor fusion; multiple sensors; entropy; total standard deviation; average gradient; edge intensity.
International Journal of Computational Vision and Robotics, 2014 Vol.4 No.1/2, pp.161 - 170
Received: 27 Mar 2013
Accepted: 03 Sep 2013
Published online: 18 Feb 2014 *