Rapid digital imaging fuzzy identification and restored image quality assessment method
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
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: 2015-03-11
严格集团股份有限公司
View PDF5 Cites 24 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
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 effect
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
specific Embodiment approach 1
[0044] 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:
[0045] Step 1: Input the gray-scale blurred image F(i,j), obtain the size M×N of the gray-scale blurred image F(i,j), and calculate the horizontal gradient image G of the gray-scale blurred image F(i,j) x (i, j) and the vertical gradient image and G y (i, j), thereby obtaining the gradient image G (i, j); wherein, M is the width of the image, and N is the height of the image;
[0046] Step 2: Calculate the average gray gradient value GMG (Gray Mean Gradients) of the image F(i, j), which reflects the gradient amplitude characteristics of the fuzzy identification index of the image;
[0047] Step 3: Perform histogram statistics on the gradient image, that is, calculate the histogram h of the gradient image G(i, j), and obtain the non-zero gray level number NGN(Non -ze...
specific Embodiment approach 2
[0059] 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:
[0060] G x ( i , j ) = | F ( i + 1 , j ) - F ( i , j ) | ...
specific Embodiment approach 3
[0061] 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:
[0062] GMG = Σ i = 1 M - 1 Σ j = 1 N - 1 [ F ( i + 1 , j...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more
PUM
Login to view more
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 restored. However, in many cases, ...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to view more 
Login to view more