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Automatic hyperspectral image exposure method and system based on COPOD algorithm

A hyperspectral image and automatic exposure technology, which is applied in the direction of image communication, TV system components, color TV components, etc., can solve the problems of large output image memory, long imaging time, and tediousness, and achieve strong adaptability and Effectiveness, Significant Difference in Imaging, Good Accuracy, and Generalization

Active Publication Date: 2022-07-22
SICHUAN JIUZHOU ELECTRIC GROUP
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the challenges of long imaging time and large output image memory, the method of manually adjusting the camera exposure time according to the sampling environment to optimize the imaging effect is backward and cumbersome.
Most of the existing automatic exposure algorithms are based on traditional RGB cameras, and it is difficult to apply to hyperspectral cameras

Method used

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  • Automatic hyperspectral image exposure method and system based on COPOD algorithm
  • Automatic hyperspectral image exposure method and system based on COPOD algorithm
  • Automatic hyperspectral image exposure method and system based on COPOD algorithm

Examples

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Effect test

Embodiment 1

[0067] Example 1: Automatic exposure method of hyperspectral image based on COPOD algorithm, such as figure 1 shown, including the following steps:

[0068] S1: Obtain a hyperspectral raw image with exposure time;

[0069] S2: Calculate the image feature vector set in each hyperspectral original image based on the K-order moment;

[0070] S3: Calculate the bilateral empirical cumulative distribution function based on the image feature vector set;

[0071] S4: Calculate the empirical Copula function based on the bilateral empirical cumulative distribution function;

[0072] S5: Estimate the two-sided tail probability value of the joint distribution on all dimensions through the empirical Copula function;

[0073] S6: Obtain the analysis result of overexposure, overdarkness or normal exposure of the hyperspectral original image according to the probability analysis of the two-sided tail;

[0074] S7: Adjust the exposure time for abnormal exposure conditions until the exposur...

Embodiment 2

[0120] Example 2: Hyperspectral image automatic exposure system based on COPOD algorithm, such as Image 6 As shown, it includes an image acquisition module, a feature calculation module, a first function module, a second function module, a probability estimation module, a result analysis module and an automatic adjustment module.

[0121] Among them, the image acquisition module is used to obtain the hyperspectral original image with exposure time; the feature calculation module is used to calculate the image feature vector set in each hyperspectral original image based on the K-order moment; the first function module is used for Calculate the two-sided empirical cumulative distribution function based on the set of image feature vectors; the second function module is used to calculate the empirical Copula function based on the two-sided empirical cumulative distribution function; the probability estimation module is used to estimate the double-sided joint distribution on all dim...

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Abstract

The invention discloses a hyperspectral image automatic exposure method and system based on a COPOD algorithm, and relates to the technical field of image preprocessing, and the technical scheme is characterized in that the method comprises the steps: obtaining a hyperspectral original image with exposure time; calculating an image feature vector set in each hyperspectral original image by taking a K-order moment as a main part; calculating a bilateral empirical cumulative distribution function based on the image feature vector set; calculating an experience Copula function based on the bilateral experience cumulative distribution function; estimating double-side tail end probability values which are jointly distributed on all dimensions through an experience Copula function; analysis results of overexposure, over-darkness or normal exposure of the original hyperspectral image are obtained according to bilateral tail end probability analysis; and adjusting the exposure time according to the abnormal exposure condition until the exposure is normal. According to the method, the feature vector of the original image and the experience Coupla function are utilized, so that good accuracy and generalization can be ensured.

Description

technical field [0001] The invention relates to the technical field of image preprocessing, and more particularly, to a hyperspectral image automatic exposure method and system based on COPOD algorithm. Background technique [0002] Hyperspectral cameras can only take full advantage of their high resolution in the spectral dimension under normal exposure conditions. However, due to the challenges of long imaging time and large output image memory, the method of manually adjusting the camera exposure time according to the sampling environment to optimize the imaging effect is backward and cumbersome. Most of the existing automatic exposure algorithms are based on traditional RGB cameras and are difficult to apply to hyperspectral cameras. Therefore, how to study and design an automatic exposure method and system for hyperspectral images based on COPOD algorithm that can overcome the above-mentioned defects is an urgent problem that we need to solve at present. SUMMARY OF T...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N5/235
CPCH04N23/73Y02A40/10
Inventor 邓尧闫超袁良垲付强刘志刚王正伟
Owner SICHUAN JIUZHOU ELECTRIC GROUP
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