Ocean remote sensing image water color and water temperature monitoring method based on compression sampling

Abstract

The invention discloses an ocean remote sensing image water color and water temperature monitoring method based on compression sampling. The monitoring method comprises the following steps of: obtaining original remote sensing data of ocean water color or water temperature to be detected, and carrying out compression sampling, sparse transformation and image processing on the original remote sensing data to obtain a water color or water temperature data set; sequentially conducting denoising and reconstruction processing on the water color or water temperature data set through an SOM (self-organized mapping) algorithm to obtain a processed water color or water temperature data set; conducting denoising processing on the processed water color or water temperature data set and reconstructing missing image data by utilizing the continuous interpolation property; and outputting and displaying the reconstructed missing image data. The monitoring method utilizes the compression sampling principle for reducing the amount of processed data, and utilizes the advantages of nonlinear estimation of the SOM algorithm as well as linear estimation and continuous interpolation of an improved empirical orthogonal decomposition (EOF) algorithm and the like so as to improve the efficiency of reconstructing missing images, expand the scope of the reconstructed images, and enable the precision and efficiency of ocean remote sensing water color and water temperature monitoring to be high.

Description

technical field [0001] The invention belongs to the field of marine monitoring, in particular to a method for monitoring water color and temperature of marine remote sensing images based on compressed sampling. Background technique [0002] With the development of science and technology, marine remote sensing technology has made great progress. As the application of satellite ocean remote sensing, the use of ocean water color and water temperature remote sensing has become more and more prominent. However, due to the impact of objective factors such as random climate changes and unsatisfactory thin cloud detection algorithms, the lack of data not only affects marine research and business work using remote sensing products. It has brought great restrictions, and because of the large amount of marine satellite remote sensing data, the application of remote sensing products has been further restricted. What's more, the lack of data has greatly reduced the monitoring area of ​​m...

AI Technical Summary

Problems solved by technology

[0004] The monitoring methods in the prior art are inefficient in reconstructing missing images, have strict requirements on the reconstructed objects, and have limitations

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