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Fusion of multifocus images by lattice structures
Affiliation:1. Department of Electrical and Electronical Engineering, Erzurum Technical University, Yakutiye 25700, Erzurum, Turkey;2. Department of Electronics and Communications Engineering, Istanbul Technical University, Maslak 34469, Istanbul, Turkey;3. Purdue University, School of Electrical and Computer Engineering, West Lafayette, IN 47907, USA;1. Department of Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;2. Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran;1. School of Software Engineering, Tongji University, Shanghai 201804, China;2. Nanyang Technological University, Singapore;1. Department of Electronics, University of Alcala, Alcalá de Henares 28801, Spain;2. Department of Mathematics and Computer Science, University of Udine, Udine 33100, Italy;1. School of Computer and Information, AnHui Polytechnic University, WuHu, AnHui 241000, China;2. Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information, Ministry of Education, Nanjing University of Science and Technology, Nanjing 210094, China
Abstract:Image fusion methods based on multiscale transform (MST) suffer from high computational load due to the use of fast Fourier transforms (ffts) in the lowpass and highpass filtering steps. Lifting wavelet scheme which is based on second generation wavelets has been proposed as a solution to this issue. Lifting Wavelet Transform (LWT) is composed of split, prediction and update operations all implemented in the spatial domain using multiplications and additions, thus computation time is highly reduced. Since image fusion performance benefits from undecimated transform, it has later been extended to Stationary Lifting Wavelet Transform (SLWT). In this paper, we propose to use the lattice filter for the MST analysis step. Lattice filter is composed of analysis and synthesis parts where simultaneous lowpass and highpass operations are performed in spatial domain with the help of additions/multiplications and delay operations, in a recursive structure which increases robustness to noise. Since the original filter is designed for the undecimated case, we have developed undecimated lattice structures, and applied them to the fusion of multifocus images. Fusion results and evaluation metrics show that the proposed method has better performance especially with noisy images while having similar computational load with LSWT based fusion method.
Keywords:Image fusion  Lifting wavelet transform  Multiscale products  Lattice filters  QMF filterbanks
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