Night lamplight image interaction radiation correction method based on stable mapping points

Abstract

The invention relates to a night lamplight image interaction radiation correction method based on stable mapping points. The night lamplight image interaction radiation correction method is characterized by comprising the following steps that firstly, night lamplight images to be corrected in an interaction radiation mode are read; secondly, a reference area is determined according to the read-in night lamplight images; thirdly, a correction reference image is determined; fourthly, the stable mapping points in the images are extracted to serve as regression calculating points of interaction correction mode parameters; fifthly, a rational function correction model between the DN value of the reference image in the regression calculating points and the mapping DN values of the images to be corrected is established, and correction parameters are obtained through calculation; sixthly, the correction parameters obtained in the fifth step are adopted to correct the images to be corrected. The night lamplight image interaction radiation correction method can be widely applied to interaction correction of a plurality of satellite sensors for night lamplight data acquired by business type line scanning sensors carrying night stable lamplight intensity image data which are not calibrated by radiation during many years.

Description

technical field [0001] The invention relates to a method for correcting mutual radiation between night light images based on stable mapping points, and belongs to the technical field of remote sensing image processing. Background technique [0002] Night light images refer to the detection of weak near-infrared radiation on the surface at night, so that night light data from cities, towns, etc. that contain persistent light sources that are not affected by sunlight can be obtained. Night light images characterize towns as blocky or patchy bright Spot areas (i.e. light areas) are clearly distinguished from dark rural backgrounds (i.e. no light areas), effectively avoiding the confusion of urban areas and non-urban areas produced by traditional remote sensing images, and providing a basis for monitoring human economic activities. A unique means of data acquisition. Compared with daytime remote sensing data, nighttime light remote sensing data has the characteristics that it i...

AI Technical Summary

Problems solved by technology

In the selection of image correction points, it has been corrected by selecting stable bright pixels on long-term images as correction points, but because the DN value of the image is only 64 levels, the DN value of the pixel in the area with large light brightness is extremely high. It is easy to be saturated, this method does not eliminate the saturation point, so the calibration point still has certain uncertainty; in addition, the constant target area method often assumes that the light brightness value of this area does not change between years, and this area has a long-term It is impossible to exist in the sequence, and it also introduces some inaccuracies in the correction points caused by the change of the actual light brightness; in the selection of the model, the quadratic polynomial is a more commonly used fitting model, but the fitting result It cannot fit all the points very well, especially the points whose DN values ​​are distributed around 0 and 63 have a certain gap in the fitting results

To sum up, there is still no accurate correction method for the problem of radiation correction between luminous remote sensing image data.

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