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MAP-MRF super-resolution image reconstruction method based on attitude information constraint

A low-resolution image and image reconstruction technology, applied in the field of MAP-MRF super-resolution image reconstruction based on attitude information constraints, can solve the problem of ineffective suppression of noise amplification, improve the singularity of the observation matrix, etc., and achieve suppression of noise amplification. , Improve the singularity of the observation matrix and the effect of highlighting the detail information

Active Publication Date: 2019-07-26
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, these methods are based on pure spectrum analysis in the mathematical sense, and cannot effectively suppress noise amplification and improve the singularity of the observation matrix

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  • MAP-MRF super-resolution image reconstruction method based on attitude information constraint
  • MAP-MRF super-resolution image reconstruction method based on attitude information constraint
  • MAP-MRF super-resolution image reconstruction method based on attitude information constraint

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[0020] The present invention will be further described in detail below in conjunction with formulas and accompanying drawings.

[0021] A MAP-MRF super-resolution image reconstruction method based on attitude information constraints proposed by the present invention, such as Figure 5 As shown, a kind of MAP-MRF super-resolution image reconstruction method based on attitude information constraints provided by the present invention comprises the following steps:

[0022] S1, modeling the change law of attitude information in the three directions of roll, pitch and yaw: Since the three-axis attitude changes fluctuate around a certain constant and are bounded, the attitude data conforms to the characteristics of a stationary time series. The pitch information of multiple frames of images is expressed as a superposition of sine (or cosine) wave signals of different frequencies:

[0023]

[0024] Among them, f(P x ) represents the smooth curve fitted by the x-axis attitude inf...

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Abstract

The invention discloses an MAP-MRF super-resolution image reconstruction method based on attitude information constraint. The method comprises the following steps: S1, carrying out modeling and calculating; s2, extracting image feature points; s3, establishing an MAP-MRF model of the image sequence; and S4, super-resolution reconstruction: carrying out fuzzy kernel estimation by using an iterativereweighted least square method, and solving an MRF optimal solution by using a belief propagation algorithm to complete super-resolution reconstruction. Compared with a traditional super-resolution image reconstruction method, the method has the advantages that attitude information constraint is added, and non-redundant space-time information is provided outside the image; the MAP-MRF model better conforms to an actual image sequence imaging model, errors caused by mismatching of a prior model can be effectively avoided, a reconstructed high-resolution image is clearer, detail information ismore prominent, noise amplification can be effectively inhibited, and the singularity problem of an observation matrix can be effectively solved.

Description

technical field [0001] The invention relates to the technical field of super-resolution image reconstruction, in particular to a MAP-MRF super-resolution image reconstruction method based on attitude information constraints. Background technique [0002] Digital optoelectronic imaging systems are widely used in imaging guidance, industrial inspection, bionic robots, aerospace remote sensing, and medical inspection. Obtaining high-resolution images of objects of interest is one of the main goals pursued by imaging systems. Due to the unavoidable undersampling effect in the imaging process of discrete sampling imaging devices such as CCD and CMOS, the resolution of the acquired image will be reduced. Image super-resolution reconstruction uses a software method to reconstruct the high-frequency signal aliased in the low-frequency signal caused by undersampling, thereby obtaining an image higher than the system resolution. [0003] Super-resolution reconstruction needs to proce...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40
CPCG06T3/4053
Inventor 高昆朱振宇张廷华韩璐豆泽阳周颖婕
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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