A no-reference image quality evaluation method based on independent component analysis

An independent component analysis and image quality technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of unsatisfactory natural image quality effect, inability to characterize image quality well, and poor subjective consistency.

Pending Publication Date: 2019-06-04
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0003] There are some defects in the existing no-reference image quality assessment technology, such as: the image quality cannot be well represented; the image quality assessment algorithm is slow; the subjective consistency is poor, etc.
In addition, an image q

Method used

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  • A no-reference image quality evaluation method based on independent component analysis
  • A no-reference image quality evaluation method based on independent component analysis
  • A no-reference image quality evaluation method based on independent component analysis

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Embodiment Construction

[0046] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0047] A no-reference image quality assessment method based on independent component analysis, including the following steps:

[0048] Step 1), for each image in the LIVE2 image library, select five image quality blocks:

[0049] Step 1.1), generate a scatterplot of each image, figure 1 (a), figure 1 (b) are the original image and scatter plot of the image respectively;

[0050] Step 1.2), calculate the spread width I of the scatter plot w ;

[0051]Step 1.3), sliding a 32×32 window on the image to obtain all 32×32 image blocks, and calculating the scatter width I of the pixel-to-scatter diagram in each image block pw ;

[0052] Step 1.4), for each image block, calculate its spreading width I p w and i w The ratio of is used as the RWID value of the image block;

[0053] Step 1.5), classify each image block according to the range of the fo...

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Abstract

The invention discloses a no-reference image quality evaluation method based on independent component analysis. The method comprises the following steps: selecting an image quality block representingimage quality by utilizing spatial correlation of pixel pairs; Using the selected optimal image quality block and adopting a Fast ICA algorithm to obtain detection characteristics of images in an LIVE2 image library, and obtaining independent components of the image quality block according to the characteristics; Establishing a hash lookup table by taking binaryzation of independent components ofan image in LIVE2 as a hash function, wherein each data element of the lookup table comprises judgment data, independent component data and a subjective quality evaluation (DMOS) value; And searchingthe hash table by using binaryzation of independent components of the image to be detected, and performing Hamming distance matching on the conflict item to obtain a no-reference image quality evaluation result. The evaluation result and the DMOS value keep good consistency, and the distortion degree of the image can be measured accurately.

Description

technical field [0001] The invention relates to the field of image quality evaluation, in particular to the technical field of communication and information processing. Background technique [0002] In the era of rapid development of digital audio-visual technology, people put forward higher requirements for the quality of transmitted and acquired images. Therefore, it is necessary to embed a quality monitoring module in the display terminal of image or video processing. In order to meet the requirements of the image processing system for quality monitoring and overcome the difficulty of obtaining standard reference images, scholars have proposed a no-reference image quality evaluation technology, and the technology has been studied in depth. [0003] The existing no-reference image quality assessment technology has some defects, such as: the image quality cannot be well represented; the image quality assessment algorithm is slow; the subjective consistency is poor and so o...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 张闯史玉华孙显文
Owner NANJING UNIV OF INFORMATION SCI & TECH
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