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Forecasting coefficient estimation method and device applicable to hyperspectral image compression

A technology of hyperspectral image and prediction coefficient, applied in the field of image processing, can solve problems such as insufficient, achieve the effect of improving compression efficiency and reducing computational complexity

Inactive Publication Date: 2010-06-02
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This method reduces the computational complexity and saves resources to a certain extent, but it is still not enough

Method used

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  • Forecasting coefficient estimation method and device applicable to hyperspectral image compression
  • Forecasting coefficient estimation method and device applicable to hyperspectral image compression
  • Forecasting coefficient estimation method and device applicable to hyperspectral image compression

Examples

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Effect test

Embodiment 1

[0062] Applying the method provided by the present invention, assuming that the predicted spectrum segment is the previous adjacent spectrum segment, by estimating the prediction coefficient, taking the spectrum segment B10-B20 of Cuprite RadianceSc1 as the example data, the first-order calculated according to the three parameter indexes respectively The prediction coefficient values ​​and the first-order prediction coefficient values ​​calculated based on all pixels are shown in Table 1:

[0063] Table 1 Values ​​of first-order prediction coefficients

[0064]

[0065]As shown in Table 1, the difference between the parameter values ​​calculated by the method of the present invention (including maximum value, minimum value and difference) and the parameter values ​​calculated by all pixels is no more than 0.08, and it is not necessary to fit all pixels, and the calculation The complexity is greatly reduced, and it is very suitable for the compression environment of hyperspe...

Embodiment 2

[0067] Assuming that the predicted spectrum segment is the previous adjacent spectrum segment, the prediction model is a linear model with a constant term of 0, and the spectrum segment B10-B20 of CupriteRadianceSc1 is used as the example data, and the peak signal-to-noise ratio PSNR is used as the measurement standard to calculate the predicted image The difference with the original image and the comparison with the results of the full-pixel prediction model are shown in Table 2. The specific calculation formula used for the peak signal-to-noise ratio is as (10):

[0068] PSNR=10log 10 (2 16 / MSE) (11)

[0069] in, MSE = { Σ x = 1 M Σ y = 1 N ( f ^ i ( ...

Embodiment 3

[0076] Assuming that the predicted spectrum section is the previous adjacent spectrum section, the prediction model is a first-order linear model (the constant term is not 0), and the spectrum section B10-B20 of CupriteRadianceSc1 is used as the example data, and the peak signal-to-noise ratio PSNR is used as the measurement standard. Table 3 shows the difference between the calculated predicted image and the original image, and the comparison with the results of the full-pixel prediction model. The specific calculation formula of the prediction model is as (14):

[0077] f ^ i ( x , y ) = f j ( x , y ) × e i , j + const - - - ...

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Abstract

The invention discloses a forecasting coefficient estimation method and a device applicable to hyperspectral image compression, belonging to the technical field of image processing. The method determines a parameter value Ci of a spectral section to be coded of a hyperspectral image, a parameter value Bj of a reference spectral section of the hyperspectral image, the ratios ei and j of the reference values of the spectral section to be coded and the reference spectral section to obtain the estimation values ei and j of the forecasting coefficient, and then hyperspectral image compression is carried out according to the estimation values. The invention can choose only one parameter to accurately calculate a first-order forecasting coefficient with very low complexity, and can fully utilize the inter-spectral relevance of hyperspectrals effectively; and combined with the prior hyperspectral compression method based on DSC and a model, the invention can simply and accurately realize the estimation of a forecasting model, thereby improving compression efficiency.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a prediction coefficient estimation method and device, in particular to a prediction coefficient estimation method and device suitable for hyperspectral image compression. Background technique [0002] With the popularization and application of imaging spectrometers, the spatial resolution and spectral resolution of remote sensing images are getting higher and higher, which makes the amount of imaging spectral data increase rapidly. Effective compression of massive data has become an urgent problem in the development of remote sensing technology. question. The spectral information of hyperspectral images is rich, and it is far from enough to remove spatial correlation. As the spectral resolution increases, and the images of different spectral bands involve the same objects, the correlation of spectral images of adjacent spectral bands becomes very close, and hyperspectral...

Claims

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Application Information

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IPC IPC(8): G01S7/48
Inventor 刘荣科王健蓉
Owner BEIHANG UNIV
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