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Hyperspectral atmosphere infrared remote sensing image lossless compression method based on quantified ICA (Independent Component Analysis)

A remote sensing image, lossless compression technology, applied in image communication, image coding, image data processing, etc., can solve the problem that the remote sensing image compression method is not applicable to hyperspectral atmospheric infrared remote sensing images, etc.

Active Publication Date: 2018-03-06
HARBIN INST OF TECH +1
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Problems solved by technology

[0003] The purpose of the present invention is to solve the problem that the existing remote sensing image compression method is not suitable for the hyperspectral atmospheric infrared remote sensing image processing process, and propose a non-destructive compression method for hyperspectral atmospheric infrared remote sensing images based on quantization ICA

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  • Hyperspectral atmosphere infrared remote sensing image lossless compression method based on quantified ICA (Independent Component Analysis)
  • Hyperspectral atmosphere infrared remote sensing image lossless compression method based on quantified ICA (Independent Component Analysis)
  • Hyperspectral atmosphere infrared remote sensing image lossless compression method based on quantified ICA (Independent Component Analysis)

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specific Embodiment approach 1

[0052] Specific implementation mode 1. Combination figure 1 Illustrate the specific embodiment of the present invention, a kind of hyperspectral atmospheric infrared remote sensing image lossless compression method based on quantitative ICA:

[0053] Step 1. The size of the three-dimensional hyperspectral atmospheric infrared remote sensing image data is M×N×L, and the total number of band channels is L. Convert it into two-dimensional, and obtain a matrix X=[x 1 ,x 2 ,...,x L ] T , where x i (1≤i≤L) is an M×N-dimensional row vector.

[0054] Then carry out zero-mean processing on it, the specific method is as follows:

[0055] order variable is the average value of all elements in each row vector of the data matrix X, namely:

[0056]

[0057] mean vector by M×N elements can be written as follows:

[0058]

[0059] Then after zero-mean processing on X, we get

[0060]

[0061] Step two, right Perform whitening processing to obtain the whitened resul...

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Abstract

The invention provides a hyperspectral atmosphere infrared remote sensing image lossless compression method based on quantified ICA (Independent Component Analysis), and aims to solve the problem thatan existing remote sensing image compression method is not suitable for a hyperspectral atmosphere infrared remote sensing image processing process. The method comprises the following steps: converting three-dimensional hyperspectral data into a two-dimensional matrix, and processing; solving a separating matrix of ICA conversion, and solving an ICA conversion coefficient matrix; then, quantifying the conversion coefficient matrix and an independent component matrix to obtain a matrix AQ and a matrix YQ, subtracting an original image from a result obtained by performing inverse quantificationand inverse ICA on the matrix AQ and the matrix YQ to obtain a residual matrix D, and predicting the AQ and the YQ to obtain a residual matrix AQP and a residual matrix YQP; and lastly, three residual matrixes D, AQP and YAP are subjected to range encoding to obtain compressed code streams. Through adoption of the method, a hyperspectral atmosphere infrared remote sensing image can be effectivelycompressed, and a relatively high compression rate is achieved.

Description

technical field [0001] The invention relates to the field of lossless compression of remote sensing images, in particular to a method for lossless compression of hyperspectral atmospheric infrared remote sensing images based on quantization ICA. Background technique [0002] With the development of hyperspectral atmospheric infrared remote sensing detection technology, the detection of the atmosphere is becoming more and more precise, and the detection cycle is getting shorter and shorter, so the data volume of detection information is also increasing. Under the circumstances, the storage and transmission of detection information is an inevitable problem in the process of data application. Therefore, in order to achieve rapid transmission of hyperspectral atmospheric infrared remote sensing image data, it is necessary to compress it to reduce data storage space. In recent years, most of the researches on the effective compression of hyperspectral atmospheric infrared remote...

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Application Information

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IPC IPC(8): H04N19/124H04N19/59H04N19/593G06T9/00
CPCG06T9/00H04N19/124H04N19/59H04N19/593
Inventor 陈浩魏安琪宿腾野滑艺
Owner HARBIN INST OF TECH
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