Image Distortion Threshold Coefficient Estimation Method Based on EEG Signal

Abstract

The invention discloses an image distortion threshold coefficient estimation method based on electroencephalogram signals, which mainly solves the problem that the prior art does not fully consider the human visual characteristics and causes the low accuracy of image quality evaluation. Image; collect the EEG signal caused by the subject's observation of the stimulus image; sequentially perform reference conversion, baseline correction, filtering and segmentation processing on the collected EEG signal; calculate the distorted image of the subject's observation on the processed EEG signal The threshold value of the EEG signal with an accuracy rate of 50% is determined, the linear relationship between the threshold value of the EEG signal of the subject and the level of image distortion is obtained, and the coefficient of the threshold value of the image distortion is estimated. The present invention fully considers the characteristics of human visual perception, uses the image distortion threshold coefficient to estimate the threshold of the EEG signal caused by the subject observing the distorted image, improves the objectivity and accuracy of image quality evaluation, and can be used for image quality evaluation and image compression and image detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to an image distortion threshold coefficient estimation method. It can be used for image quality evaluation, image compression, image detection and psychological behavior research. Background technique [0002] With the continuous development of display technology, consumers in modern society have higher and higher requirements for display technology. Not only do they require basic things such as large screens, clear images, and rich colors, but consumers begin to care more about deeper things, such as Whether it is true when watching the image, and whether it is the image quality you most hope to achieve. Because of this, the research on image quality evaluation has become a hot spot in display technology research. [0003] Image quality evaluation methods are divided into subjective evaluation and objective evaluation. Subjective evaluation uses people as observe...

AI Technical Summary

Problems solved by technology

[0007] The technical solution of the present invention is, aiming at the limitations and uncertainties existing in the existing image quality evaluation methods, resulting in insufficient consideration of the human visual characteristics, by designing the research paradigm of EEG experiments, extracting the subjects’ EEG Signal, associating EEG signals with behavioral data, estimating the perceptible thresholds of EEG signals of images with different degrees of distortion, and obtaining the relationship between the degree of image distortion and the perceivable thresholds, thereby obtaining the image distortion threshold coefficients. The implementation steps include the following:

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