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Lossless spectrum image compression method based on support vector regression

A technology of support vector regression and spectral image, applied in the field of spectral remote sensing, it can solve the problems of large amount of spectral data, difficult transmission and storage of spectral image, etc., and achieve the effect of good technical support, removal of inter-band redundancy, and high compression ratio.

Active Publication Date: 2015-01-07
XIDIAN UNIV +1
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Problems solved by technology

[0005] The purpose of the present invention is to provide a lossless compression method for spectral images based on support vector regression in view of the large amount of spectral data generated by imaging spectrometers, difficulties in transmission and storage of spectral images, and methods for effectively removing redundant spectral data.

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  • Lossless spectrum image compression method based on support vector regression
  • Lossless spectrum image compression method based on support vector regression
  • Lossless spectrum image compression method based on support vector regression

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Embodiment 1

[0041] In order to overcome the large amount of spectral data generated by current imaging spectrometers, the difficulties in transmission and storage of spectral images, and the shortcomings of methods for effectively removing spectral data redundancy, the present invention provides a method such as figure 1 , figure 2 , image 3 and Figure 4 The shown spectral image lossless compression method based on support vector regression includes the following steps:

[0042] (1) Import the spectral image, that is, the original image;

[0043] (2) Select a clustering algorithm, classify and preprocess the spectral image, and obtain the corresponding clustering index;

[0044] (3) Select the prediction algorithm, carry out the design of the prediction model, according to the clustering index that step (2) obtains and the prediction model that this step produces, predict each pixel of the whole spectrum image, obtain the prediction image;

[0045] (4) Perform a difference between ...

Embodiment 2

[0080] On the basis of Embodiment 1, the effects of the present invention are further illustrated through the following simulation experiments.

[0081] The simulation condition of the present invention: computer configuration environment is Intel (R) Core (TM) 34.00Ghz, internal memory 2G, system windows7, computer simulation software adopts the MATLABR2010a of integrated Libsvm. The experimental database uses the corrected Yellowstone hyperspectral dataset (Scene0, Scene3, Scene10, Scene11, Scene18) obtained by the American AVIRIS scanner in 2006.

[0082] Simulation content of the present invention: select one group of data in the experimental database, such as Scene0; In the simulation of this embodiment, the number of clusters selected is 16, the number of training samples of support vector regression is 300, and the prediction order is 10. In the process of training the predictive model by support vector regression, the parameters are selected as g=1, c=0.00001-1 (the st...

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Abstract

The invention belongs to the technical field of spectrum remote sensing, and provides a lossless spectrum image compression method based on support vector regression. The method comprises the following steps that firstly, an original image is guided in; secondly, a clustering algorithm is selected, classification preprocessing is carried out on the spectrum image, and a corresponding cluster index is acquired; thirdly, a prediction algorithm is selected, a prediction model is designed, and all pixels of the whole spectrum image are predicted according to the obtained cluster index and the prediction model so as to obtain a predicted image; fourthly, a differential method is adopted on the original image and the prediction image to obtain a residual image; fifthly, arithmetic coding is adopted on the residual image, the prediction coefficients obtained during prediction of the prediction model and the cluster index obtained through the clustering algorithm are coded to obtain a code stream file. According to the method, due to the fact that the read image is clustered, prediction models are established for all types, and the residual image and the side information are coded, the lossless spectrum compression based on support vector regression is achieved, a good lossless compression effect is achieved, the prediction accuracy is high, and the residual error is small.

Description

technical field [0001] The invention belongs to the technical field of spectral remote sensing, and relates to a lossless compression and coding technology of spectral images, in particular to a lossless compression method of spectral images based on support vector regression. Background technique [0002] Spectral remote sensing technology is a kind of earth observation technology that emerged in the 1980s. It is widely used in ocean remote sensing, geological exploration, atmospheric and environmental remote sensing, and military reconnaissance. With the improvement of spatial and interspectral resolution of imaging spectrometers, spectral data has increased dramatically. However, the expansion of data volume and data dimension will bring great difficulties to the transmission and storage of spectral images. Compression of spectral images is necessary. [0003] Since the imaging spectrum is imaged in a narrow spectral range, this makes the spectral image have a strong int...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/50H04N19/59
CPCG06F18/23G06F18/2411
Inventor 吴家骥白静任改玲张敏焦李成张向荣王爽熊涛刘红英
Owner XIDIAN UNIV
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