Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

Clicks: 172
ID: 85443
2009
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Abstract
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., intraurban). 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 resolutionenhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well indetail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics.
Reference Key
hu2009superresolutionsensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hu, Mao-Gui;Ge, Yong;Wang, Jin-Feng;
Journal sensors
Year 2009
DOI
DOI not found
URL
http://www.mdpi.com/1424-8220/9/11/8669/
Keywords
Chemical technology computer engineering. computer hardware electronic computers. computer science

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