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A Fast Digital Imaging Blur Identification and Restoration Image Quality Assessment Method

A technology for image quality assessment and digital imaging, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of inability to effectively identify blurred images and clear images, ineffective evaluation of image restoration results, and unstable output results. Achieve the effects of strong implementability, guaranteed reliability, and enhanced accuracy

Active Publication Date: 2017-04-19
严格集团股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0009] The purpose of the present invention is to solve the problems that the current existing methods have poor real-time performance, cannot effectively distinguish between blurred images and clear images, cannot effectively evaluate the image restoration results, and the output results are unstable after blur restoration processing, and propose a Rapid Digital Imaging Blur Identification and Restoration Image Quality Evaluation Method

Method used

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  • A Fast Digital Imaging Blur Identification and Restoration Image Quality Assessment Method
  • A Fast Digital Imaging Blur Identification and Restoration Image Quality Assessment Method
  • A Fast Digital Imaging Blur Identification and Restoration Image Quality Assessment Method

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specific Embodiment approach 1

[0042] Specific Embodiment 1: A method for rapid digital imaging blur identification and restoration image quality evaluation method of this embodiment is specifically prepared according to the following steps:

[0043] Step 1: Input the grayscale blurred image F(i,j), obtain the size M×N of the grayscale blurred image F(i,j), and calculate the horizontal gradient image G of the grayscale blurred image F(i,j) x (i, j) and the vertical gradient image G y (i,j), thereby obtaining the gradient image G(i,j); wherein, M is the width of the grayscale blurred image F(i,j), and N is the height of the grayscale blurred image F(i,j);

[0044] Step 2: Calculating the average gray gradient value GMG (Gray MeanGradients) of the grayscale blurred image F(i, j), which reflects the gradient magnitude characteristic of the blurred discrimination index of the image;

[0045] Step 3: Perform histogram statistics on the gradient image, that is, calculate the histogram h of the gradient image G(i...

specific Embodiment approach 2

[0056] Specific embodiment 2: The difference between this embodiment and specific embodiment 1 is that the gradient image G(i, j) is obtained in step 1, and the calculation formula is as follows:

[0057] Among them, i, j are the abscissa and ordinate values ​​corresponding to the image pixel, respectively. Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0058] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is: the average gray gradient value GMG formula of calculating image F (i, j) in step two is as follows:

[0059]

[0060] . Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention discloses a rapid digital imaging fuzzy identification and restored image quality assessment method, and relates to a fuzzy identification and restored image quality assessment method, for solving the problems of poor real-time performance, incapability of effective identification of a blurred image and a clear image and effective assessment of an image restoration result, and instable output result after fuzzy restoration processing by use of a conventional method. The method is realized through the following steps: 1, obtaining a gradient image G (i, j); 2, calculating an average gray scale gradient value; 3, obtaining statistical distribution information of the gradient image; 4, performing threshold determining on BIM; 5, obtaining a restored image; 6, generating reference images F1 and D1; 7, calculating brightness similarities, contrast similarities and structural similarities between the reference images and an image to be assessed; 8, calculating g(F(i, j), F1) and g(D(i, j), D1); 9, obtaining a non-reference-image assessment index; 10, determining the non-reference-image assessment index; and the like. The rapid digital imaging fuzzy identification and restored image quality assessment method is applied to the field of fuzzy identification and restored image quality assessment.

Description

technical field [0001] The invention relates to the field of image quality evaluation, in particular to the field of fuzzy identification and restoration image quality evaluation. Background technique [0002] When a digital camera is imaging, the relative movement between the lens and the imaging scene or the defocusing of the lens will cause the captured image or video to be blurred, resulting in a decrease in the contrast of the image, weakening of the edge and internal details, affecting the image quality and making it visually intuitive And the digital image information processing system is difficult to accurately detect the region of interest in the image, which seriously affects the analysis and understanding of the acquired image and video information. Generally, the image quality can be improved to a certain extent through the digital blurred image restoration system, and a part of the edge and internal details of the image can be recovered. However, in many cases,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T5/40
CPCG06T5/003G06T7/0002G06T2207/30168
Inventor 遆晓光尹磊
Owner 严格集团股份有限公司
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