A fast storage method for remote sensing data based on non-volatile memory

Abstract

The present invention provides a remote sensing data fast storage method based on a non-volatile memory, which relates to the technical field of data storage. The method includes the following steps: S1: Obtain the initial erasing address of the non-volatile memory; S2: When inputting the remote sensing data, Extract the reference image to obtain the preliminary geographic information matching value; S3: judge whether the acquaintance between the input geographic information matching value and the preliminary geographic information matching value is greater than a predetermined threshold, if so, execute step S4, otherwise, execute step S2; S4: combine the two The data corresponding to the group reference image is stored in two adjacent blocks; S5: Obtain the comparative remote sensing data again, vote, and mark the block with a low vote value; S6: When outputting the stored content, output the block that encounters the mark and skip it The marked block goes to the next block for output. The remote sensing data fast storage method based on the non-volatile memory of the present invention has fast data storage, high accuracy and small error, can perform data comparison and correction, and stores data for convenient query.

Description

technical field [0001] The present invention relates to the technical field of data storage, [0002] In particular, the invention relates to a non-volatile memory-based remote sensing data fast storage method. Background technique [0003] With the development of remote sensing technology, high spatial resolution remote sensing images have become the main data source for applications such as precision agriculture, target recognition, disaster assessment, and change monitoring. In practical applications, it is necessary to record the collected high-speed real-time data (such as high-resolution image data) in real time for post-processing. With the improvement of the accuracy of collected data and the increase of recording parameters, the amount of data to be recorded has increased sharply, and the data transmission rate has also become higher and higher. This makes the research of recording equipment in real-time, large capacity, reliability and other aspects become a hots...

AI Technical Summary

Problems solved by technology

[0004] Generally, satellites or drones are used to carry data collectors for data acquisition. Satellite data will be affected by weather, satellite revisit cycles, etc. Similarly, drones have a small range of data acquisition due to their low altitude and small viewing angle. Multiple cruises repeatedly acquire data. When the same-source images cannot completely cover the research area, we need to use multi-source remote sensing images or multiple remote sensing images.

Due to differences in collection time, platform, location, etc. and system factors, the acquired target information may have deviations, and data errors are easily generated in the rapid storage of remote sensing data, and accurate target terrain information cannot be formed.

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