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Natural scene image deblurring method integrated with non-reference image quality evaluation

A natural scene image and image quality evaluation technology, applied in the field of image processing, can solve problems such as difficulty in finding clear samples and poor adaptability of the method, and achieve the effects of overcoming the poor adaptability of the method, improving quality, and reducing the calculation scale

Active Publication Date: 2018-06-29
JIANGXI UNIV OF SCI & TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a natural scene image deblurring method that integrates non-parametric image quality evaluation, overcomes the shortcomings of difficulty in finding clear samples and poor adaptability of the method to a certain extent, and improves the quality of existing image deblurring

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  • Natural scene image deblurring method integrated with non-reference image quality evaluation
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  • Natural scene image deblurring method integrated with non-reference image quality evaluation

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Embodiment Construction

[0036] The present invention is mainly aimed at the motion blur generated in the video and image of the dynamic monitoring. For example, the vehicle-mounted camera is installed on a fixed platform, and the blur is mainly generated by the relative motion of the camera motion and the scene.

[0037] The present invention improves the existing deblurring process, introduces non-parametric image quality evaluation, and increases the image quality evaluation and optimization process after deconvolution, so that the optimal image quality can be recovered from a single blurred image without a clear reference image.

[0038] The present invention will be described in detail below in conjunction with examples.

[0039] 1. Variable mapping modeling based on spatial transformation;

[0040] 1.1 Analyze the cause of image blur, and construct a mathematical abstract model of the forward motion blur process according to the characteristics of the forward motion blur:

[0041]

[0042] A...

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Abstract

The invention relates to an image processing technology, in particular to a natural scene image deblurring method integrated with non-reference image quality evaluation. According to the method, a mathematical model of an imaging blurring process is built on the basis of analysis for image blurring causes; the model is linearized according to neighborhood graduality; independent variable mapping based on linear expansion is constructed according to the non-definite characteristic of inverse operation of the model, and calculation scale of problem solving is reduced accordingly; the non-reference image quality evaluation is introduced into the image blurring effect for evaluating an image obtained through solving, a recursive algorithm is established according to the relation between independent variables and evaluation quality indexes, and image deblurring is realized finally. With adoption of the method, defects that clear samples are difficult to find and adaptive capacity of the method is poor can be overcome to a certain degree, and existing image deblurring quality is improved.

Description

technical field [0001] The present invention relates to image processing technology, in particular to an image deblurring method that combines no-reference image quality evaluation. Background technique [0002] In the process of acquiring digital images, the image quality is degraded (degraded) due to the influence of various complex factors. These degradations include image blurring, distortion, distortion caused by optical systems, atmospheric turbulence effects, motion, etc., as well as circuit and optical factors. noise. [0003] Because the natural clear image has certain statistical characteristics, and image blurring will change this characteristic. Fergus et al [Fergus, Rob, et al. Removing camera shake from a single photograph. ACMTransactions on Graphics (TOG) [J], 25(3), 2006.] found through a large number of experiments that the gradient of natural images obeys the heavy-tailed distribution , and use a Gaussian model to approximate the heavy-tailed distributio...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
CPCG06T7/0002G06T2207/30168G06T2207/10016G06T5/73
Inventor 黄绿娥鄢化彪肖茜朱根松吴凌燕刘辉
Owner JIANGXI UNIV OF SCI & TECH
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