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Rebuilding algorithm for super-resolution remote sensing image based on fractal theory

A super-resolution, remote sensing image technology, applied in the field of geographic information science, can solve problems such as difficulty in obtaining

Inactive Publication Date: 2012-12-12
INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

The super-resolution method based on multiple images extracts complementary information between different images, and can obtain better results than single image reconstruction. However, in many practical applications, it is very difficult to obtain multiple images of the same scene. yes, even impossible

Method used

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  • Rebuilding algorithm for super-resolution remote sensing image based on fractal theory
  • Rebuilding algorithm for super-resolution remote sensing image based on fractal theory
  • Rebuilding algorithm for super-resolution remote sensing image based on fractal theory

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Embodiment approach

[0077] In conjunction with real data, the implementation of the algorithm of the present invention is briefly described as follows:

[0078] The first step is data collection and preprocessing

[0079] SRTM (Shuttle Radar Topography Mission) is a joint survey completed by NASA (National Space Administration), NGA (National Geospatial-Intelligence Agency) and the German and Italian space agencies. Interferometric radar sensors on the space shuttle Endeavor to obtain elevation data from the Earth's surface. The final released DEM data set has two spatial resolutions, that is, the grid size is 1 arc second and 3 arc seconds, which are approximately equivalent to the spatial resolution accuracy (on the equator) of 30m and 90m respectively, and the latter is based on the former processed. The area we selected is the SRTM image within the range of latitude 35.48N to 35.63N and longitude 99.68W to 99.53W (attached Figure 5 ). The size of SRTM3 (LR) is 180×180, and the size of co...

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Abstract

The invention relates to a rebuilding method for a super-resolution remote sensing image based on a fractal theory. The rebuilding method provided by the invention is as follows: connecting fractal similarity or affinity between areas under different scales in an image through fractal coding and transmitting the established connection to a spacial scale with higher resolution through the transmissibility of fractal feature on the scale. According to the invention, an image containing additive white gaussian noise is separated in a quantified way, so that a noise-free high-resolution image can be rebuilt from a noise-containing low-resolution image. The rebuilding for super resolution of a digital elevation image, the effectiveness of the rebuilding method provided by the invention is improved. A fractal-based super-resolution rebuilding model capable of removing noises provided by the invention has theoretical significance and practical value in global environment change study, disaster and environment monitoring.

Description

technical field [0001] The invention belongs to the field of geographic information science and technology, takes a single remote sensing image as the main research object, conducts super-resolution reconstruction research on it, and reconstructs the image with low spatial resolution from the existing low spatial resolution image under the condition of maintaining the original characteristics of the remote sensing image. Remote sensing images with high spatial resolution, so that the resulting image has a higher spatial resolution than the input image. Background technique [0002] How to obtain useful information of higher spatial resolution from low spatial resolution images is an important issue in the research of super-resolution image reconstruction. Super-resolution image reconstruction can be defined as a method of generating a higher spatial resolution image from one or more low spatial resolution images through analysis and processing. The output image is not only h...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 胡茂桂王劲峰赵豫
Owner INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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