A Restoration Method of Turbulent Degraded Image Based on Correlation Maximization

A degraded image and image technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of not being able to restore the image, unable to ensure the consistency of the direction of the high-frequency component and the mean image, and not applicable

Active Publication Date: 2021-06-29
TIANJIN UNIV
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Problems solved by technology

Due to the uncertainty of the eigendecomposition used by the principal component analysis method, the direction consistency between the calculated high-frequency components and the mean image cannot be guaranteed, and the desired restored image may not be obtained
In addition, this method regards the entire degraded image as a fuzzy space-invariant image, which is not suitable for actual turbulent degraded images

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  • A Restoration Method of Turbulent Degraded Image Based on Correlation Maximization
  • A Restoration Method of Turbulent Degraded Image Based on Correlation Maximization
  • A Restoration Method of Turbulent Degraded Image Based on Correlation Maximization

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Embodiment Construction

[0029] In order to make the purpose, technical solution and advantages of the present invention clearer, the implementation manners of the present invention will be further described in detail below.

[0030] Below to image 3 The degraded image shown is taken as an example, and the specific processing process of the degraded image restoration method of the present invention is set forth;

[0031] Step 1. Simulate 15 images of the lunar surface affected by turbulence g i (i=1,2,...,15, the size is 256×256 pixels), such as image 3 As shown in (a), calculate its mean image For the mean image φ, the Laplacian filter is used for enhancement processing, such as image 3 As shown in (c), set it as the reference image Ψ;

[0032] Step 2. For each g i The image and the reference image Ψ are divided into 16 sub-module images whose size is 106×106 pixels, and the interval between two adjacent sub-modules is nexp=50 pixels, such as image 3 (a) shown. Then, the sub-module images...

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Abstract

The invention discloses a turbulent degraded image restoration method based on correlation maximization. image, and then group the sub-module images at the corresponding positions into a sub-image set; calculate the Euclidean distance between each sub-module image in each sub-image set and the sub-module image in the reference image set, which will be smaller than the median distance. The sub-module images are then formed into a new image set; the final restored sub-module image is obtained from the new image set based on the principal component analysis method and the maximum similarity feature of the image; then the final restored sub-module image is extracted according to the corresponding sub-image set. The positions form an image, which is the resulting restored image. The method divides the collected multi-frame images and the corresponding reference images into multiple sub-module image sets with blurred image space unchanged, which is suitable for actual turbulent degraded images.

Description

technical field [0001] The invention relates to a degraded image restoration method, in particular to an atmospheric turbulent image restoration problem, and belongs to the field of multi-frame turbulent image restoration. Background technique [0002] In medium and long-distance imaging systems, the atmospheric turbulence phenomenon caused by the influence of wind speed and temperature causes irregular changes in the refractive index of the propagation medium, resulting in distortion of light waves when propagating in the medium, resulting in geometric deformation and blurring of the collected images. Therefore, effectively restoring the original target image from the turbulence-degraded image is one of the key issues to realize the processing of target detection and recognition. [0003] The commonly used turbulent degraded image restoration methods are mainly based on single-frame and multi-frame turbulent image restoration methods. Due to the strong randomness of turbul...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T5/50G06T7/10
CPCG06T5/002G06T5/50G06T7/10
Inventor 吕且妮斯那卓玛葛宝臻田庆国
Owner TIANJIN UNIV
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