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Time dimension compression method for hyperspectral atmospheric infrared remote sensing image

A remote sensing image and compression method technology, applied in image communication, color/spectral characteristic measurement, electrical components, etc., can solve problems such as poor image compression effect and failure to consider correlation laws and related characteristics.

Active Publication Date: 2020-04-21
HARBIN INST OF TECH
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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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  • Time dimension compression method for hyperspectral atmospheric infrared remote sensing image
  • Time dimension compression method for hyperspectral atmospheric infrared remote sensing image
  • Time dimension compression method for hyperspectral atmospheric infrared remote sensing image

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[0058] The technical solutions and effects of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0059] In the experiment, the time-dimensional data obtained by the Interferometric Atmospheric Vertical Sounder (GIIRS) carried on the Fengyun-4 geostationary orbit meteorological satellite independently developed by my country was used. GIIRS infrared atmospheric images cover two spectral bands, which are 14.28-8.85μm (700-1130cm -1 ) long wave band and 6.06~4.45μm (1650~2250cm -1 ) in the short-wave band, and the spectral resolution is 0.625. The atmospheric content detected in different wavelength ranges is different. Figure 10 shows the spectral coverage of GIIRS.

[0060] The experimental data selects hyperspectral images of 10 moments in the long-wave band (the data size is 32×4×689, 32×4 is the spatial scale, that is, the number of 128 probes arranged in 32×4, and 689 is the number of spectral channels in the long-wave...

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Abstract

The invention discloses a time dimension compression method for a hyperspectral atmospheric infrared remote sensing image, and belongs to the technical field of remote sensing image compression. The hyperspectral atmospheric image compression method solves the problem that the existing hyperspectral atmospheric image compression method does not consider that the correlation rule between differenttime slices under large-range complex movement of the atmosphere is different from the correlation characteristic between high-frame-rate video frames, so that the image compression effect is poor. Based on the characteristic that hyperspectral infrared atmospheric image data detected by a detector in the same scene at different time have large correlation, a time dimension compression scheme of the hyperspectral infrared atmospheric image is designed based on an online learning prediction model. A prediction model from reference time slice images at different moments to a time slice image ata middle moment is established through a self-adaptive online updating prediction model, and prediction model parameters are updated in real time according to an online learning theory, so that multi-time slice image compression of hyperspectral data is realized, and the average compression ratio reaches 9.42. The inventioncan be applied to remote sensing image compression.

Description

technical field [0001] The invention belongs to the technical field of compression of remote sensing images, and in particular relates to a time dimension compression method of 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 detection. At present, several hyperspectral detectors are operating in polar orbits. The first hyperspectral atmospheric sounder, AIRS, was launched by the United States in 2002. It has 2378 channels in the infrared 3.7-15.4μm range and a sub-satellite point resolution of 13km. 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 satelli...

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Application Information

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IPC IPC(8): H04N19/503H04N19/42H04N19/182H04N19/105G01N21/17G01N21/35
CPCH04N19/503H04N19/42H04N19/182H04N19/105G01N21/17G01N21/35G01N2021/1795G01N2021/1785Y02A90/10
Inventor 陈浩高萌萌陈瑾怡
Owner HARBIN INST OF TECH
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