Abstract
Pan-sharpening aims at integrating spectral information from a multi-spectral (MS) image and spatial information from a panchromatic (PAN) image in a fused image with both high spectral and spatial resolutions. Numerous pan-sharpening methods are based on intensity-hue-saturation (IHS) transform, which may cause evident spectral distortion. To address this problem, an IHS-based pan-sharpening method using ripplet transform and compressed sensing is proposed. Firstly, the IHS transform is applied to the MS image to separate intensity components. Secondly, discrete ripplet transform (DRT) is implemented on the intensity component and the PAN image to obtain multi-scale sub-images. High-frequency sub-images are fused by a local variance algorithm and, for low-frequency sub-images, compressed sensing is introduced for the reconstruction of the intensity component so as to integrate the local information from both the intensity component and the PAN image. The specific fusion rule is defined by local difference. Finally, the inverse ripplet transform and inverse IHS transform are coupled to generate the pan-sharpened image. The proposed method is compared with five state-of-the-art pan-sharpening methods and also the Gram-Schmidt (GS) method through visual and quantitative analysis of WorldView-2, Pleiades and Triplesat datasets. The experimental results reveal that the proposed method achieves relatively higher spatial resolution and more desirable spectral fidelity.
Highlights
Remote sensing (RS) is a general approach for the knowledge extraction of the Earth’s surface structure and content through acquiring and interpreting the spectral characteristics from a great distance [1]
Experimental results on WorldView-2, Pleiades-1A, and Triplesat data are reported in Tables 6–8, separately
The results indicate that the proposed method achieves better spectral fidelity while yielding greater spatial information improvement than the other state-of-the-art methods
Summary
Remote sensing (RS) is a general approach for the knowledge extraction of the Earth’s surface structure and content through acquiring and interpreting the spectral characteristics from a great distance [1]. The well-known trade-off between spatial resolution and spectral resolution has always precluded the further application of RS products. Pan-sharpening is a desirable solution to settle such dilemma. Most of the Earth observation satellite images, such as IKONOS, QuickBird, and the WorldView family (including WorldView-2/3/4), can only provide a panchromatic (PAN) image with high spatial resolution but low spectral resolution together, with a multi-spectral (MS) image with low spatial resolution but high spectral resolution, respectively [2]. Pan-sharpening, a special case of image fusion, is capable of obtaining an image with both high spatial and high spectral resolutions. The technique provides a fused image with the same spectral response as the MS image and with the spatial resolution of the PAN image.
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