A Time-Dimension Compression Method for Hyperspectral Atmospheric Infrared Remote Sensing Images

Abstract

The invention discloses a time-dimension compression method of hyperspectral atmospheric infrared remote sensing image, which belongs to the technical field of remote sensing image compression. The invention solves the problem that the existing hyperspectral atmospheric image compression method does not take into account that the correlation law between different time slices under the large-scale complex movement of the atmosphere is different from the correlation characteristics between high frame rate video frames, resulting in poor image compression effect. Based on the characteristics of the large correlation between the hyperspectral infrared atmospheric image data detected by the detector at different times on the same scene, a time-dimension compression scheme for hyperspectral infrared atmospheric image based on an online learning prediction model is designed. Through an adaptive online Update the prediction model, establish a prediction model from the reference time slice image at different times to the time slice image at the intermediate time, and update the prediction model parameters in real time according to the online learning theory, so as to realize the image compression of hyperspectral data in multiple time slices, average The compression ratio reaches 9.42. The invention can be applied to the compression of remote sensing images.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image compression, in particular to a time-dimensional compression method for hyperspectral atmospheric infrared remote sensing images. Background technique [0002] In recent years, hyperspectral atmospheric infrared remote sensing images have become one of the main data sources for satellite atmospheric exploration. Several hyperspectral detectors are currently operating in polar orbits. The first hyperspectral atmospheric sounder, AIRS, was launched and operated by the United States in 2002. It has 2,378 channels in the infrared range of 3.7-15.4 μm and a sub-satellite point resolution of 13 km. In 2006, the IASI detector launched by the European Meteorological Satellite Application Organization has a total of 8461 channels in the range of 3.62-15.5μm, and the sub-satellite point resolution is 12km. In 2011, the United States launched a new generation of polar-orbiting meteorological s...

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing hyperspectral atmospheric image compression method does not consider that the correlation law between different time slices under the large-scale and complex movement of the atmosphere is different from the correlation characteristics between high frame rate video frames, resulting in poor image compression effect. Good question, while proposing a time-dimensional compression method for hyperspectral atmospheric infrared remote sensing images

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