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Image absolute ambiguity estimation method based on multi-scale reorganized DCT coefficients

A ambiguity estimation and multi-scale technology, applied in the field of electronic information, can solve the problems of high complexity and large computing resource consumption, and achieve the effect of small calculation, simple calculation and high accuracy

Active Publication Date: 2014-07-16
NAT UNIV OF DEFENSE TECH
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AI Technical Summary

Problems solved by technology

[0005] The general image blur evaluation method has high complexity and requires a large consumption of computing resources.

Method used

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  • Image absolute ambiguity estimation method based on multi-scale reorganized DCT coefficients
  • Image absolute ambiguity estimation method based on multi-scale reorganized DCT coefficients
  • Image absolute ambiguity estimation method based on multi-scale reorganized DCT coefficients

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Embodiment Construction

[0023] The blurriness estimation idea of ​​the present invention is that when the image is blurred, certain types of edge points such as roof edges and step edges will be significantly reduced, and the corresponding image blur can be estimated by analyzing the changes of blurred roof edges and step edge points.

[0024] The realization steps of the present invention are as follows:

[0025] 1) Perform 8×8 block DCT transformation on the image of interest, and divide each 8×8 block of 64 coefficients into three levels (similar to three levels of discrete wavelet transform) with a total of 10 coefficient sub-blocks (see figure 2 ), where the first level includes 7, 8, and 9 sub-blocks (respectively corresponding to the first-level HL, LH, and HH coefficient blocks of discrete wavelet transform), and each sub-block contains 16 coefficients, a total of 48 coefficients; the second level Including the 4th, 5th, and 6th sub-blocks (corresponding to the second-level HL, LH, and HH co...

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Abstract

The invention discloses an image absolute ambiguity estimation method based on multi-scale reorganized DCT coefficients. DCT in 8*8 blocks is carried out on an interested image, and sixty-four coefficients of 8*8 blocks are divided into three scales and comprise ten coefficient sub-blocks. The coefficient sub-blocks of the same 8*8 DCT blocks are combined together and placed at the corresponding positions, and then a reorganized three-level multi-scale DCT coefficient image is obtained. An energy image of each level is built, the edge points in the energy images are found, all roof edge point, step edge points and fuzzy edge points are found, and the absolute ambiguity of the images is calculated according to the number of the roof edge point, the step edge points and the fuzzy edge points. The absolute ambiguity is calculated through the three-level multi-scale reorganized DCT coefficients, the accuracy is high, calculation is easy, the calculated amount is small, and the method is applicable to hardware implementation.

Description

technical field [0001] The invention relates to the field of electronic information subjects, in particular to an image absolute blur estimation method based on multi-scale recombined DCT coefficients. Background technique [0002] Image blur calculation is an important issue in the field of image processing and analysis, and has applications in many aspects such as image compression coding, image quality assessment, and image-based passive focusing. [0003] Image blur evaluation is a kind of image quality evaluation, which can be divided into subjective evaluation and objective evaluation. Subjective evaluation is based on human eye observation and comparison of subjective scoring, and is obtained by collecting a certain number of scoring samples. In many applications, people are the ultimate users of image or video output, and their subjective feelings and evaluations of images are considered to be the most reliable. The shortcomings of subjective evaluation are obvious...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 张茂军张政谭树人王炜徐玮熊志辉刘煜
Owner NAT UNIV OF DEFENSE TECH
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