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Image regularization super-resolution reconstruction method based on Gaussian blur-like kernel

A Gaussian blur kernel, high-resolution technology, applied in the field of vision processing, can solve problems such as large simulation matching errors, and achieve the effect of improving the effect and wide adaptability

Pending Publication Date: 2021-03-12
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0016] In order to solve the problem that the existing point spread function form in the image super-resolution process cannot effectively approximate the actual degradation process, that is, there is a large simulation matching error with the actual degradation function model, the present invention provides a Gaussian-like blur kernel based The image regularization super-resolution reconstruction method comprehensively considers the distortion and disturbance factors, that is, the matching error between the existing model and the actual degradation, uses a Gaussian-like function model to model the blurring effect caused by the actual degradation, and takes the minimum mean square error as the criterion Super-resolution reconstruction of images

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  • Image regularization super-resolution reconstruction method based on Gaussian blur-like kernel

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[0047] The present invention will be further described below in conjunction with the accompanying drawings.

[0048] refer to Figure 1 to Figure 6 , an image regularization super-resolution reconstruction method based on a Gaussian blur kernel, comprising the following steps:

[0049] Step 1: Denoising preprocessing, for the low-resolution image sequence g degraded due to the incompatibility of the optical system itself k ∈ R M×N Carry out denoising preprocessing, where k is the number of image sequences. For different optical systems, due to the different image degradation processes, it is necessary to use appropriate filters for denoising processing. The better the denoising effect, the better the subsequent Super-resolution image reconstruction;

[0050] Step 2: Select a frame g in the low-resolution sequence image 0 As a reference, other images g in the sequence are analyzed by optical flow method l Perform sub-pixel registration to generate registration parameters F...

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Abstract

The invention discloses an image regularization super-resolution reconstruction method based on a Gaussian-like fuzzy kernel, and the method comprises the steps: comprehensively considering distortionand disturbance factors, i.e., a matching error between an existing model and actual degradation, carrying out the modeling of a fuzzy effect caused by the actual degradation by employing a Gaussian-like function model, and carrying out the super-resolution reconstruction of an image through a minimum mean square error as a criterion. According to the method, four parameters are adopted to specifically describe the objective fuzzy process, the objective fuzzy process is closer to the actual fuzzy situation, the model is obtained through theoretical analysis and experimental results, the modelis used in a deblurring algorithm, and the image reconstruction effect is improved.

Description

technical field [0001] The invention relates to the technical field of visual processing, in particular to a method for image regularization super-resolution reconstruction of an improved fuzzy function. Background technique [0002] An image is a two-dimensional representation of a high-resolution scene. It can directly or indirectly affect the visual perception of the human eye. How to improve image quality has become a research hotspot for scholars in recent years. A core indicator for evaluating image quality is image resolution. . Due to the influence of aberration and noise during the image acquisition process, as well as the motion blur between the camera and the scene, distortion will inevitably occur during the imaging process, which will affect the resolution of the image. In order to obtain high-resolution images. First of all, the most direct method is to improve the level of hardware, reduce the size of the sensor, and increase the arrangement density of the s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06T5/00G06T5/50
CPCG06T3/4053G06T5/50G06T5/73G06T5/70
Inventor 黄国兴刘艺鹏卢为党彭宏
Owner ZHEJIANG UNIV OF TECH
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