A detection method of clouds and shadows under clouds in gf-4 satellite sequence images

Abstract

The present invention is directed to the radiation pretreatment applications of high-definition No.4 satellite images, particularly the applications of cloud and below-cloud shadow detection, which provides a cloud and below-cloud shadow detection method for high-definition No.4 satellite sequence images. According to the invention, for sequence images in the same geographic region, the images are relatively rectified by different linear functions, and are ordered according to the average earth-surface radiation brightness. Meanwhile, the radiation difference caused by different acquisition times can be reduced through normalizing the linear relative radiation. According to the number of sequence images, an S-G filtering-based algorithm is selected, or the cloud and below-cloud shadow is marked according to the statistical-based automatic threshold method. Moreover, the detection result of a shadow image element is corrected according to the distance between the detected shadow image element and a nearest cloud image element. The critical step of the present invention is realized through adopting a mature algorithm, so that the stability and the applicability are relatively high. The method provides a key technical support for the production of cloud and below-cloud shadow detection products and the precision improvement of the products during the high-definition No.4 satellite data pretreatment process.

Description

technical field [0001] The invention relates to a remote sensing image radiation processing technology, in particular to a cloud and cloud shadow detection technology for high-resolution remote sensing satellite sequence images. Background technique [0002] Radiation preprocessing of remote sensing images has always been one of the main topics in remote sensing data processing. After the new remote sensing satellites are put into use, the preprocessing of the new data is an urgent issue. The preprocessing of remote sensing images usually includes geometric preprocessing and radiometric preprocessing. In addition to the key radiometric calibration, the statistics of image cloud cover is also an important step in radiometric preprocessing. According to the needs of satellite data users, the proportion of cloud cover has become an important indicator for selecting satellite images. For example, images with as little cloud cover as possible are used in classification and mappi...

AI Technical Summary

Problems solved by technology

[0005] Through the analysis and experiments on the specific data of GF-4, it is found that the mid-wave infrared data is difficult to be used for fine cloud detection. Pixel block, a total of 64 visible light pixels with a resolution of 50 meters; the geographical coverage does not overlap and the pixel size is different, the mid-wave infrared is 1204×1024 pixels, and the visible light is 10240×10240 pixels; there is a difference in imaging time, mid-wave infrared and visible light The image is designed to be imaged at a fixed interval of 45 seconds, and the movement characteristics of the cloud make the position and shape of the cloud in the two data different; in terms of data quality, there is still an obvious noise problem in the imaging of the mid-wave infrared camera

Images