Remote sensing image missing data restoration method based on multi-image local interpolation

Abstract

The invention discloses a remote sensing image missing data restoration method based on multi-image local interpolation. According to the method, based on the principle that satellite remote sensing image pixels and identical ground object pixels within a local range around the satellite remote sensing image pixels have similar spectral features, a missing data pixel is searched for in a to-be-restored image, and windows with a preset maximum search size are constructed respectively with the location of the pixel and the location of a corresponding pixel in a non-missing-data image being center points; the spectral features of pixels, corresponding to pixels with values in the window of the to-be-restored image, in the non-missing-data image are classified in the non-missing-data image to determine the location of the pixel in a minimum spectral difference with the center pixel; the spectral value of the pixel at the same location in the window of the to-be-restored image is used to replace a missing spectral value of the center point pixel in the window of the to-be-restored image; and the non-missing-data image is adopted to determine whether the missing data pixel in the to-be-restored image is the same as a certain non-missing-data pixel in a local window or has a maximum spectral similarity, and the spectral value of the non-missing-data pixel is used to fill up the spectral value of the missing data pixel. In this way, complicated calculation such as regression statistical analysis, image segmentation and geostatistical analysis on the to-be-restored image is avoided, and the method has the advantages that calculation efficiency is moderate, restoration precision is high, and the method is fast and easy to realize.

Description

Technical field: [0001] The invention relates to the technical field of image computer restoration, in particular to a method for repairing missing data of remote sensing images based on multi-image local interpolation. This method is based on the fact that spatially adjacent pixels in remote sensing images are usually similar ground objects, so spatially adjacent pixels usually have strong spectral similarity. Class relationship or spectral similarity, estimate the value of the missing data pixel in the image to be filled; the invention can be used to quickly and effectively repair the missing data in the remote sensing image, improve the utilization rate of the remote sensing image, and is based on multi-temporal remote sensing Time-series analysis of images provides a restoration and correction method for basic data. Background technique: [0002] At present, there are thousands of land resource remote sensing satellites in the world, and the images of the earth's surfac...

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Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art, and provide a remote sensing image missing data repair method based on multi-image local interpolation, which mainly solves the problem that the traditional method cannot take into account repair accuracy and repair efficiency, and does not fully consider the same The uncertainty of the spectrum of ground objects in images of different time phases cannot be applied to the problem of quantitative remote sensing research

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