Image definition evaluation method

A technology of image clarity and evaluation methods, applied in image analysis, image data processing, instruments, etc., can solve the problems of inconvenient and effective evaluation methods, and achieve the effect of convenient evaluation and simplified calculation process

Active Publication Date: 2013-03-13
KONFOONG BIOTECH INT
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] In view of the above-mentioned problems in the prior art, the technical problem to be solved by the present invention is that the existing evaluation methods are not convenient and effective enough

Method used

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Experimental program
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Effect test

Embodiment 1

[0030] Such as figure 1 As shown in , where the abscissa is the number of the image, and the ordinate is the value of the image calculated by each function relative to the resolution of 100. By selecting 21 images and numbering them sequentially from 1 to 21, the sharpness was calculated using TenenGrad function, Brenner function, variance function, square gradient function, Vollath function, windowed gradient function and entropy function. Calculate the weighted average of the data values ​​of the individual functions for each image, and calculate the weighted average of the data values ​​of the TenenGrad function and the Vollath function with a weighted weight ratio of 7:3.

[0031] It can be seen from the figure that the values ​​of the TenenGrad function, square gradient function, and windowed gradient function are almost on the same curve; the curves of the data values ​​of the TenenGrad function and the Vollath function with a weight ratio of 7:3 and the data values ​​of...

Embodiment 2

[0033] Such as figure 2 As shown in , where the abscissa is the number of the image, and the ordinate is the value of the image calculated by each function relative to the resolution of 100. By selecting 28 images and numbering them sequentially from 1 to 28, the sharpness was calculated using TenenGrad function, Brenner function, variance function, square gradient function, Vollath function, windowed gradient function and entropy function. Calculate the weighted average of the data values ​​of the individual functions for each image, and calculate the weighted average of the data values ​​of the TenenGrad function and the Vollath function with a weighted weight ratio of 7:3.

[0034] It can be seen from the figure that the curves of the data values ​​of the TenenGrad function and the Vollath function with a weight ratio of 7:3 tend to be consistent with the curves of the weighted average of the data values ​​of each function. And the clarity obtained is consistent with the ...

Embodiment 3

[0036] Such as image 3 As shown in , where the abscissa is the number of the image, and the ordinate is the value of the image calculated by each function relative to the resolution of 100. By selecting 28 images and numbering them sequentially from 1 to 28, the sharpness was calculated using TenenGrad function, Brenner function, variance function, square gradient function, Vollath function, windowed gradient function and entropy function. Calculate the weighted average of the data values ​​of the individual functions for each image, and calculate the weighted average of the data values ​​of the TenenGrad function and the Vollath function with a weighted weight ratio of 7:3.

[0037] It can be seen from the figure that the curves of the data values ​​of the TenenGrad function and the Vollath function with a weight ratio of 7:3 tend to be consistent with the curves of the weighted average of the data values ​​of each function. And the clarity obtained is consistent with the o...

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Abstract

The invention provides an image definition evaluation method comprising the following steps of: 1, carrying out data calculation on images by using image evaluation functions; 2, integrating all the calculated values of data of all the image evaluation functions; and 3, evaluating the definitions of the images by integrating the calculated values. The image definition evaluation method provided by the invention is more accurate than a single value through integrating the data of all the evaluation functions; and furthermore, the combined TenenGrad function and Vollath function are applied so that the calculation process is simplified and convenience is brought for evaluation. The image definition evaluation method is convenient, fast and efficient and capable of ensuring that an evaluation result is consistent with a result observed through human eyes.

Description

technical field [0001] The invention relates to a method for evaluating sharpness, in particular to an evaluation method for image sharpness which is evaluated by applying a function. Background technique [0002] With the development of digital imaging technology towards automation and intelligence, the application range of autofocus technology has been continuously expanded, and great progress has been made in automation, high precision, high stability, etc., and it has been widely used in cameras, video cameras, microscopes, etc. , scanners and other precision instruments. [0003] Image sharpness evaluation is of great significance in image analysis and recognition. Digital image evaluation function is an important basis for evaluating digital image definition, and is the key to realize automatic focus in digital image acquisition system. Focusing performance depends on the accuracy and real-time performance of the image evaluation function, that is, the image evaluati...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 刘炳宪谢菊元王焱辉王克惠郝美蓉
Owner KONFOONG BIOTECH INT
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