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Method for eliminating stripe noise of infrared image

A stripe noise and infrared image technology, applied in the field of image processing, can solve problems such as low-rank constraints are not very effective, image space redundancy is high, and the process of solving low-rank constraint problems is complicated, so as to reduce computational complexity and eliminate stripes noise effect

Active Publication Date: 2020-10-16
NORTHWESTERN POLYTECHNICAL UNIV
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AI Technical Summary

Problems solved by technology

When different columns of pixels in the focal plane array read out different column channels in the circuit, they are affected by time drift / temperature drift, and the amplifiers in each column channel have different noise characteristics, resulting in a large number of generated infrared images. Stripe noise. Stripe noise has the characteristics that the noise intensity on each column is roughly the same, but the noise intensity is different between different columns. The traditional filter denoising algorithm cannot grasp this feature well.
In the document "Chang Y, Yan L, Zhong S.Transformed Low-Rank Model for Line Pattern Noise Removal[C] / / 2017IEEE International Conference on Computer Vision (ICCV).IEEE,2017." A low-rank constraint is proposed The denoising algorithm can better describe the stripe noise, but due to the high redundancy of the image space, the low-rank constraint is not very effective, and the process of solving the low-rank constraint problem is more complicated

Method used

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  • Method for eliminating stripe noise of infrared image
  • Method for eliminating stripe noise of infrared image
  • Method for eliminating stripe noise of infrared image

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Experimental program
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Embodiment

[0073] For the input infrared image containing streak noise, such as figure 1 As shown, first establish a mathematical model according to step 1.

[0074] Initialize Y, a, λ 1 ,λ 2 , energy, thresh and other variables.

[0075] Construct the objective function according to the established mathematical model:

[0076]

[0077] s.t.a T *a=energy

[0078] Among them, energy is a scalar, and a reasonable value can be set according to the strength of the noise. f(Y) adopts the TV model, in order to facilitate the solution, the first norm in the TV model is changed to the second norm, namely:

[0079]

[0080] where λ 1 ,λ 2 is a scalar, representing the penalty item, Represents the convolution operation, h and d represent the horizontal gradient operator and the vertical gradient operator respectively, and the convolution operation is written in the form of matrix multiplication, then f(Y) is expressed as:

[0081]

[0082] Then use step 3 to solve the objective...

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Abstract

The invention discloses a method for eliminating stripe noise of an infrared image. The method comprises the following steps: firstly, establishing a mathematic model of an infrared image with superimposed stripe noise, visually representing the characteristics of the stripe noise through the mathematic model, then constructing an objective function, and then solving the objective function by adopting an alternate optimization method, so that the stripe noise in the infrared image can be well eliminated, and the operation complexity is reduced.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a method for eliminating noise. Background technique [0002] The uncooled infrared focal plane array receives the thermal radiation information of objects in the field of view and converts it into an infrared image, which is the current mainstream infrared thermal radiation imaging detector. When different columns of pixels in the focal plane array read out different column channels in the circuit, they are affected by time drift / temperature drift, and the amplifiers in each column channel have different noise characteristics, resulting in a large number of generated infrared images. Streak noise. Streak noise has the characteristic that the intensity of noise on each column is roughly the same, but the intensity of noise between different columns is different. The traditional filter denoising algorithm cannot grasp this feature well. In the document "Chang Y, Yan L,...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/10048G06T5/70
Inventor 王向宇梁军利
Owner NORTHWESTERN POLYTECHNICAL UNIV
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