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.
Highlights
The development of earth resources’ satellites is mainly focus on improving spatial and spectral resolutions [1]
Most optical sensors are capable of acquiring high spatial resolution panchromatic (Pan) and low spatial resolution MS bands simultaneously; for example, QuickBird, IKONOS, and SPOT series
Liu et al [21] used a bidimensional Empirical mode decomposition (EMD) method in image fusion; the results demonstrate that the EMD method may preserve both spatial and spectral information
Summary
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. Intensity-Hue-Saturation (IHS) [3] transform is one of the famous fusion algorithms using the projection-substitution method. This method interpolates MS image into the spatial resolution of a panchromatic image and converts the MS image according to intensity, hue, and saturation bands. The intensity of the MS image is replaced with a high-spatial panchromatic image and reversed to red, green, and blue bands. This method is limited to three-band images
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