Three-dimensional image quality objective evaluation method based on visual fidelity

Abstract

The invention discloses a three-dimensional image quality objective evaluation method based on visual fidelity. The method includes: in a training stage, selecting multiple original distortionless three-dimensional images to form a training image set, determining whether pixel points in the distortionless three-dimensional images belong to a shielding area or a matching area through area detection, and structuring a monocular vision dictionary table and a binocular vision dictionary table to the training image set through an unsupervised learning mode; in a testing stage, for testing three-dimensional images and the original distortionless three-dimensional images, estimating sparse coefficient array of each subblock, belonging to the shielding area and the matching area, in the testing three-dimensional images and the corresponding distortionless three-dimensional images according to the monocular vision dictionary table and the binocular vision dictionary table, calculating monocular image quality objective evaluation prediction value and binocular image quality objective evaluation prediction value through the sparse coefficient array, and finally combining to acquire an image quality evaluation predication value. The three-dimensional image quality objective evaluation method has the advantage that the acquired image quality objective evaluation predication value is highly uniform with a subjective evaluation value.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to an objective evaluation method for stereoscopic image quality based on visual fidelity. Background technique [0002] With the rapid development of image coding technology and stereoscopic display technology, stereoscopic image technology has received more and more attention and applications, and has become a current research hotspot. Stereoscopic image technology utilizes the principle of binocular parallax of the human eye. Both eyes independently receive left and right viewpoint images from the same scene, and form binocular parallax through brain fusion, so as to enjoy stereoscopic images with a sense of depth and realism. . Compared with single-channel images, stereo images need to ensure the image quality of two channels at the same time, so it is very important to evaluate its quality. However, there is currently no effective objective evaluation method to evaluate t...

AI Technical Summary

Problems solved by technology

At present, the existing method is to predict the evaluation model through machine learning, but its computational complexity is high, and the training model needs to predict the subjective evaluation value of each evaluation image, which is not suitable for practical applications and has certain limitations.

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