Remote sensing image real-time correction method and correction device

Abstract

The invention relates to a remote sensing image real-time correction method and correction device. The method comprises the following steps that a correction database is established, wherein the correction database includes a target comparison parameter table; the remote sensing image data transmitted by the sensor are received in real time, the code value of the remote sensing image data is extracted and normalization correction is performed on the code value of the remote sensing image data according to the target comparison parameter table; and the corrected remote sensing image is outputted. According to the method and the device, the remote sensing image transmitted by the sensor is received in real time and compared with the target comparison parameter table and the image is accordingly corrected so that the deviation problem of the remote sensing image, such as the stripe phenomenon, can be solved, and the method and the device are stable and reliable and low in time complexitywithout influencing quantitative application.

Description

technical field [0001] The invention relates to the technical field of signal and information processing, in particular to a real-time correction method and correction device for remote sensing images. Background technique [0002] Multivariate cross-track scanning imaging remote sensing data generally have stripes and bands are very common. Such phenomena exist in the original images uploaded by the Moderate Resolution Spectral Imager (MERSI) of Fengyun-3 (FY-3). Among them, the fringe phenomenon is the image discontinuity between rows in a frame of image (10 rows and 2048 columns), which is mainly caused by the inconsistency of the radiation response of multiple detectors. The banding phenomenon is the discontinuity of light and shade between two adjacent frames of images, which is mainly caused by the slight difference in the reflectivity of the 0-side and 1-side of the K mirror inside the resolution spectrum imager. [0003] At present, there are generally three proces...

AI Technical Summary

Problems solved by technology

This method can greatly suppress the streaks, but it cannot solve the banding phenomenon

The second is based on computer image algorithm elimination, such as wavelet transform, median filter, etc. These algorithms can get a good effect of eliminating stripes and strips for a single image. The disadvantage is that the algorithm relies on the image itself to extract correction parameters, but these The parameters are not stable enough to meet the requirements of automatic processing. At the same time, due to the nonlinear processing of the image, the reflectance information contained in the processed image will change irreversibly, which will introduce errors that are difficult to quantitatively evaluate for subsequent quantitative applications.

In terms of time complexity, different algorithms take different time, but they often affect the processing time of business systems

The third method is the matching method of empirical distribution function. This method has been discussed a lot. In practical applications, it is often only for the statistical information of a single image, and the information obtained for the ultra-low reflectivity and ultra-high reflectivity in the limit state ,Not good enough

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