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No-reference image definition detection method

A technology of image clarity and detection method, applied in the field of image processing, can solve the problems of inconsistency in definition, missed detection of video images, and inconspicuous distinction.

Active Publication Date: 2012-11-28
ZHEJIANG ICARE VISION TECH
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  • Abstract
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Problems solved by technology

[0004] The patent "image processing device, image processing method, program, and storage medium (patent number: 200710137014)" determines the focus state by the sharpness, length and direction of the edge of the object; its disadvantage is that the sharpness estimated by the image with less edge information inconsistent with subjective
The patent "A Method for Measuring Image Sharpness Using Multi-scale Morphological Features (Patent No.: 201110167446)" obtains multi-scale morphological features on the pixel gray value of the image as a measure of sharpness; its disadvantage is that for common Video images with thin stripes or noise interference can easily cause missed detection
The patent "A Method and Device for Image Quality Evaluation (Patent No.: 201010532192)" uses spatial frequency domain characteristic parameters, brightness response nonlinear characteristic parameters, masking effect characteristic parameters, etc. as human visual characteristic parameters, and uses self-learning classification method to train Human visual evaluation model; its disadvantage is that the spatial frequency domain characteristics of the image do not distinguish noise and texture clearly, the performance of the classifier is limited by the number of samples, and the output of the classifier is the image quality level, not the score value
The patent "A method for evaluating the degree of blur without a reference image (Patent No.: 201110252220)" utilizes the local characteristics of the blur effect to reflect the overall deviation between the gray value of each pixel and the gray value of surrounding pixels through the sum of the variance of the gray value of each local area The degree of deviation is normalized to obtain the final blur; its disadvantage is that it is easy to cause false detection for video images with a narrow gray scale range
The patent "image processing device and method for determining image quality (patent number: 200610115947)" uses the brightness histogram of the image to judge the image quality; its disadvantage is that the estimation result is easily affected by the image content
The patent "Intelligent Video Diagnosis Monitoring System (Patent No.: 201020660598)" mentions the use of the average gradient method to reflect the degree of subtle image contrast; its disadvantage is that the sharpness estimation result is easily affected by noise

Method used

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Embodiment Construction

[0022] In order to clearly illustrate the technical route and solution of the present invention, the specific implementation of each step in the present invention will be described in detail in conjunction with the accompanying drawings by taking the definition detection of an image as an example. These examples are illustrative, not limiting of the invention.

[0023] Step 1: Calculate the gradient map {Gx, Gy} according to the existing grayscale image; use the public edge detection algorithm to locate strong edge points.

[0024] The gradient map uses common gradient operators such as Sobel, and the edge detection algorithm can use Canny edge detection operators. Strong edge points are edge pixels detected by the edge detection algorithm.

[0025] Step 2: Calculate the edge width of the strong edge point, and count the cumulative edge width histogram EdgeWidthHist.

[0026] The calculation of the edge width, such as figure 1 As shown, at a strong edge point, compare the ab...

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Abstract

The invention relates to a no-reference image definition detection method. The method comprises the following steps of: firstly, calculating a gradient map according to the existing grey-scale map; secondly, positioning strong edge points by using an open edge detection algorithm; thirdly, calculating the edge width of each strong edge point to obtain an edge width cumulative histogram; fourthly, carrying out wavelet transform on the existing gray-scale map, and calculating the energy of high-frequency wavelet coefficient; fifthly, counting a grey-scale histogram according to the existing grey-scale map, and calculating the feature of the grey-scale histogram according to the grey-scale histogram; and finally, estimating the definition of the grey-scale map according to the edge width cumulative histogram, the energy of high-frequency wavelet coefficient and the feature of the grey-scale histogram. According to the method, the definition of images can be detected without reference images, and the definition value is consistent with the subjective feeling of eyes. The method is not influenced by the image content and the luminance of the field of view, and the detection result has a certain robustness to interferences such as coding and noise.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a reference-free image definition detection method. Background technique [0002] In practical applications, images captured by video cameras or cameras are often degraded due to various reasons, resulting in blurred and unclear visual experience of the human eye. Common reasons for image degradation are: compression, sensor performance degradation, electromagnetic interference, out of focus, etc. Image quality includes two aspects: subjective quality and objective quality. Subjective quality refers to the human eye's perception of the overall content and details of the image; objective quality refers to the degree of deviation between the degraded image and the original image. [0003] According to the degree of dependence on the original image, image quality assessment methods are mainly divided into three categories: full-reference, semi-reference and no-reference ima...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 尚凌辉林国锡王亚利高勇
Owner ZHEJIANG ICARE VISION TECH
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