Neural network nonuniformity correction method based on scene statistics

A non-uniformity correction and neural network technology, applied in radiation pyrometry, measuring devices, instruments, etc., can solve problems such as difficult to eliminate low-frequency spatial noise

Inactive Publication Date: 2010-03-10
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0012] Aiming at the change of response characteristics and stability of infrared focal plane array caused by complex and changeable environmental conditions, and the difficulty of eliminatin...

Method used

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  • Neural network nonuniformity correction method based on scene statistics
  • Neural network nonuniformity correction method based on scene statistics
  • Neural network nonuniformity correction method based on scene statistics

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Embodiment Construction

[0027] The following first analyzes the implementation process of the algorithm in principle:

[0028] A linear model is used to correct the infrared focal plane array, and the correction model is:

[0029] Y i，j (n)=G i，j (n) X i，j (n)+O i，j (n) (1)

[0030] where Y i，j Indicates the corrected output, X i，j Denotes the original image input, G i，j Indicates the correction gain, O i，j Indicates corrected image bias.

[0031] Taking expectation on both sides of the above formula can get an expression of the following form:

[0032] E[Y i，j ] = G i，j (n)·E[X i，j ]+O i，j (n) (2)

[0033] Where E[] is the expectation operator, E[Y i，j ] is the mean value of the corrected output, E[X i，j ] Input the mean value for the original image,

[0034] After subtracting formula (1) and formula (2), the following formula is obtained:

[0035] Y i，j (n)-E[Y i，j ] = G i，j (n)·(X i，j (n)-E[X i，j ]) (3)

[0036] Comparing formula (3) with formula (1), it can be seen that E[X ...

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Abstract

The invention requests to protect a neural network nonuniformity correction method based on scene statistics, belonging to the infrared focal plane detection field. The invention provides the method aiming at the shortcoming that the traditional neural network correction method is difficult to eliminate low-frequency spatial noises. The method comprises the following steps: initializing image related matrices and parameters; detecting and compensating blind pixels according to the image pixel gray value; carrying out nonuniformity correction on image offset by a scene statistics method; judging the regional attributes of the pixels by a neural network correction method according to the standard deviation thresholds of correction errors, and carrying out nonlinear gain correction on the images which are corrected based on scene statistics and contain no low-frequency spatial noises. By the method, the correction effects of the desired image signals are good, target fade-out and ghostingare inhibited, and the changes of the background images hardly affect the correction effects. The method can be widely applied to image detection and processing.

Description

technical field [0001] The invention relates to the technical field of image detection and processing, in particular to an image correction method in the infrared focal plane detection technology. Background technique [0002] Infrared focal plane array imaging system has become the development trend of infrared imaging technology due to its advantages of high sensitivity, small size, compact structure, long range, good anti-interference, strong ability to penetrate smoke, and can work all-weather and all-day. , and the staring infrared focal plane array has become the mainstream detection device for the development of future infrared thermal imaging systems. However, due to the limitations of materials and technology levels, there is generally non-uniformity among the response characteristics of each detection unit of the infrared focal plane array (IRFPA), which will lead to a significant decrease in the performance of the infrared imaging system such as temperature resolu...

Claims

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Application Information

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IPC IPC(8): G01J5/00
Inventor 代少升吴传玺张天骐将清平
Owner CHONGQING UNIV OF POSTS & TELECOMM
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