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

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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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 quality evaluation technique similar to this method is to use the statistical model of pixel pairs to evaluate image quality, but this method can only achieve good results in low-light image quality evaluation, and the effect on natural image quality is not ideal.

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