Downward-looking scene matching area selection criteria intervention method

Abstract

The invention provides a downward-looking scene matching area selection criteria intervention method. The method comprises the following steps of 1) selecting a training set; 2) carrying out characteristic extraction on the selected training set so as to acquire a characteristic quantity; 3) inputting the characteristic quantity and a classification label corresponding to the characteristic quantity into a SVM classifier to carry out learning training so as to establish a corresponding classification decision model; 4) acquiring an image to be measured, and carrying out partitioning processing on the image so as to acquire a subblock image; 5) carrying out characteristic extraction on the subblock image; 6) inputting a characteristic extracted from the sub-block image into the classification decision model to carry out classification decision; determining whether each subblock is covered by a cloud layer, and if the each subblock is covered by the cloud layer, marking as 1, and changing the corresponding subblock image into black in an original graph; otherwise, retaining the subblock image; and (7) outputting the image whose classification is determined. The method possesses characteristics that easy operability is possessed; practicality is good; and efficiency is high.

Description

technical field [0001] The invention belongs to the field of downward-looking scene matching methods, and relates to a selection criterion intervention method suitable for downward-looking scene matching. Background technique [0002] The downward-looking image matching and positioning method is to use the imager of the aircraft to capture the lower image in real time and match it with the satellite visible light matching area pre-stored in the aircraft, and determine the position of the real-time image in the satellite visible light matching area image to achieve the purpose of all-day positioning and navigation. Satellite visible light images have been widely used for their advantages of high imaging definition, objective and rich information, timeliness and practicability. However, if the satellite visible light matching area images pre-stored in the aircraft contain factors that are not conducive to matching such as clouds, the occlusion of the clouds will reduce the ava...

AI Technical Summary

Problems solved by technology

[0004] At present, the existing scene matching area selection method cannot effectively eliminate the image of the scene matching area containing clouds, and needs to be manually interpreted and analyzed to eliminate the images containing clouds

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