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	Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis
	Ge Y.
	2009
关键词	super-resolution reconstruction multifractal analysis information transfer fractal code gaussian upscaling land-cover model turbulence
英文摘要	Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e. g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics.
出处	Sensors
卷	9
期	11
页	8669-8683
收录类别	SCI
语种	英语
ISSN号	1424-8220
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/23859]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Ge Y.. Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis. 2009.

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