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Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis
Hu M. G.; Wang J. F.; Ge Y.
Source PublicationSensors
2009
Volume9
Issue11
Pages8669-8683
KeywordSuper-resolution Reconstruction Multifractal Analysis Information Transfer Fractal Code Gaussian Upscaling Land-cover Model Turbulence
AbstractSatellite 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.
Indexed BySCI
Language英语
ISSN1424-8220
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/23859
Collection历年回溯文献
Recommended Citation
GB/T 7714
Hu M. G.,Wang J. F.,Ge Y.. Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis. 2009.
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