Quantitative Evaluation Method of Stripe Noise in Remote Sensing Image

Abstract

The invention provides a quantitative evaluation method of remote sensing image stripe noise. The quantitative evaluation method comprises the following steps: reading evaluated remote sensing image attribute data, obtaining the line number data and the row number data of the pixel of the remote sensing image attribute data, obtaining the line mean value difference and the row mean value difference of an image DN (Digital Number) value through calculation according to a one-dimensional array model of a line or row; then, inputting the line mean value difference and the row mean value difference of the image DN value, and outputting the line mean value difference and the row mean value difference as the standard difference of the line or row; thirdly, inputting the line mean value difference and the row mean value difference of the image DN value, and obtaining a difference index of an image picture element through calculation; and finally, according to the output [Delta]v or [Delta]u value of the difference index of the image picture element, comparing a remote sensing image stripe noise level. The quantitative evaluation method can objectively evaluate the image stripe noise level, is convenient for laterally comparing different types of images, provides a quantitative reference index for remote sending data quality evaluation and a stripe elimination algorithm effect, can guarantee the effectiveness and the accuracy of the obtained remote sensing image data and is convenient to screen and utilize the remote sensing image.

Description

technical field [0001] The invention relates to an image processing algorithm, which belongs to the technical field of remote sensing image application, in particular to a method for quantitatively evaluating strip noise of remote sensing images. Background technique [0002] Due to the influence of imaging methods, performance of photoelectric components, and environmental parameters (such as temperature) during imaging, remote sensing images often have band noise. The existence of band noise makes remote sensing images have problems in both qualitative and quantitative use. In qualitative remote sensing interpretation and interpretation, band noise seriously affects the identification and extraction of ground object types by operators; During the inversion, the band noise will distort the radiation information. Due to the lack of quantitative indicators that can objectively reflect the degree of this distortion, its impact on the inversion results cannot be evaluated. [...

AI Technical Summary

Problems solved by technology

This method can better solve the processing of dynamic images, but the quantitative evaluation effect on band noise is limited

[0005] Chinese patent (application publication number CN104680541A) discloses "a remote sensing image quality evaluation method based on phase consistency". The invention uses comprehensive evaluation values ​​to evaluate the band noise of remote sensing images, which has no reference and comprehensive evaluation of remote sensing image quality advantages, but its comprehensive evaluation value is not accurate enough, and it is not possible to make horizontal comparisons between different types of images, and the quantitative evaluation effect on band noise is poor.

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