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No-reference blurred image evaluation method based on local statistical characteristics of images

A technology of local statistics and blurred images, applied in the field of image processing, can solve the problems of high algorithm complexity and low execution efficiency, and achieve the effect of small calculation amount, improved evaluation performance, and easy hardware implementation.

Inactive Publication Date: 2013-06-12
JIANGNAN UNIV
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Problems solved by technology

This method involves complex wavelet transform and phase calculation, the algorithm complexity is high, and the execution efficiency is low

Method used

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  • No-reference blurred image evaluation method based on local statistical characteristics of images
  • No-reference blurred image evaluation method based on local statistical characteristics of images
  • No-reference blurred image evaluation method based on local statistical characteristics of images

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with accompanying drawing and example. The evaluation method related to the quality of blurred images without reference can be used for evaluation and processing of image blurring degree in image and video related applications. The fuzzy image no-reference evaluation method based on image local statistical features in the present invention constructs a measurement scale through local statistical features of the test image and the edge area of ​​the re-blurred image. The specific process is as follows: figure 1 shown.

[0029] (1) Select a set of local regions

[0030] Use the Sobel operator to detect the edge pixels of the original image to be tested, and then assign each edge pixel to the center of a pixel block.

[0031] The smallest pixel block surrounding an edge point is 3×3. We divide this 3×3 pixel block into four smaller sets of pixels, called sub-regions, such as figure 2 shown.

[0032]...

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Abstract

The invention discloses a no-reference blurred image evaluation method based on local statistical characteristics of images, mainly solving the problem of no-reference objective evaluation of the blurred images. The method comprises the following steps: (1) firstly generating a blurred image on the image to be tested by filtering; (2) detecting the edge of the original image to be tested by the Sobel operator and selecting the local area set surrounding the edge points; (3) carrying out statistics on variation of the original image and the generated blurred image according to the selected local areas; (4) properly adjusting the variation statistics of the local areas; and (5) constructing an evaluation metric of the blurred image according to the variation statistics. The method has the advantages of simple structure, low computational complexity, easy hardware implementation and consistence with subjective evaluation and can be used for detecting effectiveness of the image and video processing method.

Description

technical field [0001] The invention relates to a non-reference evaluation method for fuzzy images based on local statistical characteristics of images, and belongs to the technical field of image processing. Background technique [0002] With the development of computer network and communication technology, digital images have become an important medium for people to obtain information and communicate and interact. Digital images are prone to various distortions in the process of acquisition, compression, processing, transmission and reproduction, and image quality is the main index to measure these distortions. There are subjective methods and objective methods for evaluating image quality. Since the ultimate observer of the image is a human being, the subjective method is highly reliable, but the subjective method is time-consuming and laborious and is not easy to be embedded in an automated system, so the objective method is the current quality evaluation method. focus....

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N17/00
Inventor 李朝锋袁万立吉训生吴小俊桑庆兵
Owner JIANGNAN UNIV
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