Tuyển tập các báo cáo nghiên cứu khoa học ngành toán học được đăng trên tạp chí toán học quốc tế đề tài: Pyramid-based image empirical mode decomposition for the fusion of multispectral and panchromatic images | Teo and Lau EURASIP Journal on Advances in Signal Processing 2012 2012 4 http content 2012 1 4 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Pyramid-based image empirical mode decomposition for the fusion of multispectral and panchromatic images Tee-Ann Teo1 and Chi-Chung Lau2 Abstract Image fusion is a fundamental technique for integrating high-resolution panchromatic images and low-resolution multispectral MS images. Fused images may enhance image interpretation. Empirical mode decomposition EMD is an effective method of decomposing non-stationary signals into a set of intrinsic mode functions IMFs . Hence the characteristics of EMD may apply to image fusion techniques. This study proposes a novel image fusion method using a pyramid-based EMD. To improve computational time the pyramid-based EMD extracts the IMF from the reduced layer. Next EMD-based image fusion decomposes the panchromatic and MS images into IMFs. The high-frequency IMF of the MS image is subsequently replaced by the high-frequency IMF of the panchromatic image. Finally the fused image is reconstructed from the mixed IMFs. Two experiments with different sensors were conducted to validate the fused results of the proposed method. The experimental results indicate that the proposed method is effective and promising regarding both visual effects and quantitative analysis. Keywords image enhancement image processing multiresolution techniques empirical mode decomposition image fusion 1. Introduction The development of earth resources satellites is mainly focus on improving spatial and spectral resolutions 1 . As the spatial and spectral information are the two critical factors for enriching the capability of image interpretation fusion of high spatial and high spectral images may increase the usability of satellite images. Most remote sensing applications such as image interpretation and feature extraction require both spatial .
