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Remote Sens. 2017, 9(4), 391; doi:10.3390/rs9040391

A Novel Pan-Sharpening Framework Based on Matting Model and Multiscale Transform

1
School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330032, China
2
School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang 330032, China
3
Institute of Biomedical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Academic Editors: Guoqing Zhou and Prasad S. Thenkabail
Received: 9 February 2017 / Revised: 10 April 2017 / Accepted: 16 April 2017 / Published: 21 April 2017
View Full-Text   |   Download PDF [14257 KB, uploaded 21 April 2017]   |  

Abstract

Pan-sharpening aims to sharpen a low spatial resolution multispectral (MS) image by combining the spatial detail information extracted from a panchromatic (PAN) image. An effective pan-sharpening method should produce a high spatial resolution MS image while preserving more spectral information. Unlike traditional intensity-hue-saturation (IHS)- and principal component analysis (PCA)-based multiscale transform methods, a novel pan-sharpening framework based on the matting model (MM) and multiscale transform is presented in this paper. First, we use the intensity component (I) of the MS image as the alpha channel to generate the spectral foreground and background. Then, an appropriate multiscale transform is utilized to fuse the PAN image and the upsampled I component to obtain the fused high-resolution gray image. In the fusion, two preeminent fusion rules are proposed to fuse the low- and high-frequency coefficients in the transform domain. Finally, the high-resolution sharpened MS image is obtained by linearly compositing the fused gray image with the upsampled foreground and background images. The proposed framework is the first work in the pan-sharpening field. A large number of experiments were tested on various satellite datasets; the subjective visual and objective evaluation results indicate that the proposed method performs better than the IHS- and PCA-based frameworks, as well as other state-of-the-art pan-sharpening methods both in terms of spatial quality and spectral maintenance. View Full-Text
Keywords: pan-sharpening; matting model; multiscale transform; image fusion pan-sharpening; matting model; multiscale transform; image fusion
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yang, Y.; Wan, W.; Huang, S.; Lin, P.; Que, Y. A Novel Pan-Sharpening Framework Based on Matting Model and Multiscale Transform. Remote Sens. 2017, 9, 391.

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