Relative radiometric correction method for automatically extracting pseudo-invariant features for remote sensing image

Abstract

For multi-spectral space remote sensing data in a visible light and near-infrared range, the invention provides a relative radiometric correction technology for automatically extracting pseudo-invariant feature points for a remote sensing image. The technology mainly comprises the following steps of: for a target image with a digital number (DN) value, searching a matched reference image with surface reflectivity; pre-processing the two images; by using a canonical correlation analysis technology, searching a canonical correlation point set; screening the pseudo-invariant feature points in the canonical correlation point set; and by using the pseudo-invariant feature points, fitting a linear relation, and by using the linear relation, performing linear relative radiometric correction processing on the target image. By adoption of an algorithm, the DN value of the target image is directly converted into the surface reflectivity. The algorithm has the characteristics of simple processing flow, high processing speed and stability, and manual interaction is not required; moreover, the algorithm can be used for relative radiometric correction of the same sensors or different sensors and is particularly applicable to radiometric processing of remote sensing data, wherein the auxiliary information of the remote sensing data is lost or calibration accuracy is low, and absolute radiometric correction is not suitable for the remote sensing data.

Description

technical field [0001] The invention relates to a remote sensing image radiation correction technology, in particular to a remote sensing image relative radiation correction technology for automatically extracting pseudo-invariant features. Background technique [0002] Radiometric correction of remote sensing images has always been one of the main difficulties in remote sensing data processing. In recent years, with the rapid development of quantitative remote sensing technology, especially the wide application of multi-sensor and multi-temporal remote sensing data for land use and land cover change monitoring, global resource and environment analysis, and climate change monitoring, the radiometric correction method of remote sensing images research is gaining more and more attention. The current radiometric correction methods for remote sensing images can be divided into two categories, Absolute Radiometric Correction and Relative Radiometric Correction. [0003] Absolut...

AI Technical Summary

Problems solved by technology

There are many PIFs extraction algorithms at present, and the main problems include strong human-computer interaction, poor data versatility, and low robustness, etc.

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